# How to integrate Parseur MCP with LlamaIndex ```json { "title": "How to integrate Parseur MCP with LlamaIndex", "toolkit": "Parseur", "toolkit_slug": "parseur", "framework": "LlamaIndex", "framework_slug": "llama-index", "url": "https://composio.dev/toolkits/parseur/framework/llama-index", "markdown_url": "https://composio.dev/toolkits/parseur/framework/llama-index.md", "updated_at": "2026-05-12T10:21:25.959Z" } ``` ## Introduction This guide walks you through connecting Parseur to LlamaIndex using the Composio tool router. By the end, you'll have a working Parseur agent that can list all documents in your invoices mailbox, create a webhook to send parsed receipts, pause the outgoing webhook for orders mailbox through natural language commands. This guide will help you understand how to give your LlamaIndex agent real control over a Parseur account through Composio's Parseur MCP server. Before we dive in, let's take a quick look at the key ideas and tools involved. ## Also integrate Parseur with - [OpenAI Agents SDK](https://composio.dev/toolkits/parseur/framework/open-ai-agents-sdk) - [Claude Agent SDK](https://composio.dev/toolkits/parseur/framework/claude-agents-sdk) - [Claude Code](https://composio.dev/toolkits/parseur/framework/claude-code) - [Claude Cowork](https://composio.dev/toolkits/parseur/framework/claude-cowork) - [Codex](https://composio.dev/toolkits/parseur/framework/codex) - [OpenClaw](https://composio.dev/toolkits/parseur/framework/openclaw) - [Hermes](https://composio.dev/toolkits/parseur/framework/hermes-agent) - [CLI](https://composio.dev/toolkits/parseur/framework/cli) - [Google ADK](https://composio.dev/toolkits/parseur/framework/google-adk) - [LangChain](https://composio.dev/toolkits/parseur/framework/langchain) - [Vercel AI SDK](https://composio.dev/toolkits/parseur/framework/ai-sdk) - [Mastra AI](https://composio.dev/toolkits/parseur/framework/mastra-ai) - [CrewAI](https://composio.dev/toolkits/parseur/framework/crew-ai) ## TL;DR Here's what you'll learn: - Set your OpenAI and Composio API keys - Install LlamaIndex and Composio packages - Create a Composio Tool Router session for Parseur - Connect LlamaIndex to the Parseur MCP server - Build a Parseur-powered agent using LlamaIndex - Interact with Parseur through natural language ## What is LlamaIndex? LlamaIndex is a data framework for building LLM applications. It provides tools for connecting LLMs to external data sources and services through agents and tools. Key features include: - ReAct Agent: Reasoning and acting pattern for tool-using agents - MCP Tools: Native support for Model Context Protocol - Context Management: Maintain conversation context across interactions - Async Support: Built for async/await patterns ## What is the Parseur MCP server, and what's possible with it? The Parseur MCP server is an implementation of the Model Context Protocol that connects your AI agent and assistants like Claude, Cursor, etc directly to your Parseur account. It provides structured and secure access to your Parseur data extraction workflows, so your agent can perform actions like managing mailboxes, handling documents, configuring webhooks, and automating template operations on your behalf. - Mailbox management and discovery: Let your agent list, browse, and filter all Parseur mailboxes to keep tabs on your parsing operations and document streams. - Document listing and retrieval: Effortlessly fetch documents from specific mailboxes, enabling automated sorting, searching, or pagination of your parsed files. - Template and parsing rule automation: Ask your agent to list templates within any mailbox, so you can quickly inspect or update parsing rules as your data extraction needs evolve. - Webhook configuration and control: Enable your agent to create, update, pause, enable, or delete webhooks, making it easy to automate real-time data delivery to your other systems. - Comprehensive webhook inspection: Retrieve detailed webhook information or list all webhooks for a mailbox, ensuring you always know how and where your parsed data is flowing. ## Supported Tools | Tool slug | Name | Description | |---|---|---| | `PARSEUR_COPY_DOCUMENT` | Copy Document | Tool to copy a document to another mailbox. Use when you need to duplicate a document from one mailbox to another mailbox within Parseur. | | `PARSEUR_COPY_MAILBOX` | Copy Mailbox | Tool to copy a mailbox (parser) in Parseur. Creates a duplicate of the mailbox with all its configuration. Use when you need to duplicate an existing parser setup. | | `PARSEUR_CREATE_CUSTOM_DOWNLOAD` | Create custom download | Tool to create a custom download (export configuration) for a mailbox. Use when you need to define which fields should be exported to CSV or XLS format. | | `PARSEUR_CREATE_MAILBOX` | Create mailbox | Tool to create a new mailbox (parser) in Parseur. Use when you need to set up a new parser for document parsing with custom configuration. | | `PARSEUR_DELETE_CUSTOM_DOWNLOAD` | Delete custom download | Tool to delete a custom download (export configuration) from a mailbox. Use when permanently removing an export configuration after confirming its ID. | | `PARSEUR_DELETE_DOCUMENT` | Delete document | Tool to delete a specific document by ID. Use when permanently removing a document after confirming its ID. | | `PARSEUR_DELETE_MAILBOX` | Delete mailbox | Tool to delete a mailbox (parser) by ID. Use when permanently removing a mailbox after confirming its ID. | | `PARSEUR_DELETE_WEBHOOK` | Delete webhook | Tool to delete a specific webhook. Use when permanently removing a webhook after confirming its ID. | | `PARSEUR_DISABLE_WEBHOOK` | Disable webhook | Tool to disable a webhook for a mailbox. Removes the webhook association from the specified mailbox. Use when you need to stop an active webhook from sending parsed data. | | `PARSEUR_ENABLE_WEBHOOK` | Enable webhook | Enables a paused webhook for a specified mailbox, allowing it to receive and forward parsed document events. Use this action to re-enable a webhook that was previously paused. Only webhooks listed in 'available_webhook_set' (paused webhooks) can be enabled. After enabling, the webhook will appear in 'webhook_set' (active webhooks) and begin sending HTTP POST requests to its target URL when the configured event occurs (e.g., document.processed). | | `PARSEUR_GET_BOOTSTRAP_CONFIG` | Get Bootstrap Config | Tool to retrieve bootstrap configuration data. Use when you need system-wide configuration choices, field format mappings, maximum field lengths, or master parser definitions. | | `PARSEUR_GET_DOCUMENT` | Get Document | Tool to retrieve full details of a specific document by ID. Returns document status, processing info, parsed results, and download URLs for JSON, CSV, and XLS formats. | | `PARSEUR_GET_DOCUMENT_LOGS` | Get Document Logs | Tool to get document logs for a specific document. Returns paginated list of logs with status, source, and message details. Use when you need to troubleshoot or audit document processing history. | | `PARSEUR_GET_MAILBOX` | Get Mailbox by ID | Tool to retrieve full mailbox (parser) configuration by ID. Use when you need complete details about a specific mailbox including fields, webhooks, and settings. | | `PARSEUR_GET_MAILBOX_SCHEMA` | Get Mailbox Schema | Tool to retrieve the JSON schema for a mailbox's parsed fields. Use when you need to understand the structure and types of data fields extracted by a specific parser. | | `PARSEUR_LIST_CUSTOM_DOWNLOADS` | List Custom Downloads | Tool to retrieve custom downloads (export configurations) for a mailbox. Use when you need to list available export formats and their download URLs. | | `PARSEUR_LIST_DOCUMENTS_IN_MAILBOX` | List Documents in Mailbox | Tool to list documents within a specific mailbox. Use when you need to paginate, search, or sort the documents of a given mailbox after obtaining its ID. | | `PARSEUR_LIST_MAILBOXES2` | List Mailboxes (Full Details) | Tool to list mailboxes (parsers) with full configuration details. Returns paginated list of all mailboxes with document counts, processing statistics, and complete configuration settings. Use when you need comprehensive mailbox information including field configurations, processing options, and webhook settings. | | `PARSEUR_LIST_TEMPLATES` | List Templates for Mailbox | Tool to list all templates in a given mailbox. Use after fetching mailbox details when you need to page through and inspect available templates for further actions. | | `PARSEUR_REPROCESS_DOCUMENT` | Reprocess a document | Tool to reprocess a document. Triggers re-parsing of the document with the current template configuration. Use when you need to re-parse a document after template updates or to retry failed parsing. | | `PARSEUR_RETRIEVE_WEBHOOK` | Retrieve a webhook | Tool to retrieve details of a specific webhook. Use after creating or listing webhooks. | | `PARSEUR_SKIP_DOCUMENT` | Skip a document | Tool to skip a document. Marks the document as skipped and returns the updated document with status 'SKIPPED'. | | `PARSEUR_UPDATE_CUSTOM_DOWNLOAD` | Update custom download | Tool to update a custom download (export configuration) for a mailbox. Use when you need to modify the field list, name, or export settings for an existing download configuration. | | `PARSEUR_UPDATE_MAILBOX` | Update Mailbox | Tool to update a mailbox (parser) configuration. Use when you need to modify mailbox settings such as name, AI engine, processing options, or document handling rules. | | `PARSEUR_UPDATE_WEBHOOK` | Update webhook | Tool to update an existing webhook’s settings. Use when you need to change the webhook’s target URL, event type, headers, or name after creation. | | `PARSEUR_UPLOAD_EMAIL_DOCUMENT` | Upload Email Document | Tool to upload an email or text document to Parseur for parsing. Use when you need to programmatically send documents to a Parseur mailbox. | ## Supported Triggers None listed. ## Creating MCP Server - Stand-alone vs Composio SDK The Parseur MCP server is an implementation of the Model Context Protocol that connects your AI agent to Parseur. It provides structured and secure access so your agent can perform Parseur operations on your behalf through a secure, permission-based interface. With Composio's managed implementation, you don't have to create your own developer app. For production, if you're building an end product, we recommend using your own credentials. The managed server helps you prototype fast and go from 0-1 faster. ## Step-by-step Guide ### 1. Prerequisites Before you begin, make sure you have: - Python 3.8/Node 16 or higher installed - A Composio account with the API key - An OpenAI API key - A Parseur account and project - Basic familiarity with async Python/Typescript ### 1. Getting API Keys for OpenAI, Composio, and Parseur No description provided. ### 2. Installing dependencies No description provided. ```python pip install composio-llamaindex llama-index llama-index-llms-openai llama-index-tools-mcp python-dotenv ``` ```typescript npm install @composio/llamaindex @llamaindex/openai @llamaindex/tools @llamaindex/workflow dotenv ``` ### 3. Set environment variables Create a .env file in your project root: These credentials will be used to: - Authenticate with OpenAI's GPT-5 model - Connect to Composio's Tool Router - Identify your Composio user session for Parseur access ```bash OPENAI_API_KEY=your-openai-api-key COMPOSIO_API_KEY=your-composio-api-key COMPOSIO_USER_ID=your-user-id ``` ### 4. Import modules No description provided. ```python import asyncio import os import dotenv from composio import Composio from composio_llamaindex import LlamaIndexProvider from llama_index.core.agent.workflow import ReActAgent from llama_index.core.workflow import Context from llama_index.llms.openai import OpenAI from llama_index.tools.mcp import BasicMCPClient, McpToolSpec dotenv.load_dotenv() ``` ```typescript import "dotenv/config"; import readline from "node:readline/promises"; import { stdin as input, stdout as output } from "node:process"; import { Composio } from "@composio/core"; import { mcp } from "@llamaindex/tools"; import { agent as createAgent } from "@llamaindex/workflow"; import { openai } from "@llamaindex/openai"; dotenv.config(); ``` ### 5. Load environment variables and initialize Composio No description provided. ```python OPENAI_API_KEY = os.getenv("OPENAI_API_KEY") COMPOSIO_API_KEY = os.getenv("COMPOSIO_API_KEY") COMPOSIO_USER_ID = os.getenv("COMPOSIO_USER_ID") if not OPENAI_API_KEY: raise ValueError("OPENAI_API_KEY is not set in the environment") if not COMPOSIO_API_KEY: raise ValueError("COMPOSIO_API_KEY is not set in the environment") if not COMPOSIO_USER_ID: raise ValueError("COMPOSIO_USER_ID is not set in the environment") ``` ```typescript const OPENAI_API_KEY = process.env.OPENAI_API_KEY; const COMPOSIO_API_KEY = process.env.COMPOSIO_API_KEY; const COMPOSIO_USER_ID = process.env.COMPOSIO_USER_ID; if (!OPENAI_API_KEY) throw new Error("OPENAI_API_KEY is not set"); if (!COMPOSIO_API_KEY) throw new Error("COMPOSIO_API_KEY is not set"); if (!COMPOSIO_USER_ID) throw new Error("COMPOSIO_USER_ID is not set"); ``` ### 6. Create a Tool Router session and build the agent function What's happening here: - We create a Composio client using your API key and configure it with the LlamaIndex provider - We then create a tool router MCP session for your user, specifying the toolkits we want to use (in this case, parseur) - The session returns an MCP HTTP endpoint URL that acts as a gateway to all your configured tools - LlamaIndex will connect to this endpoint to dynamically discover and use the available Parseur tools. - The MCP tools are mapped to LlamaIndex-compatible tools and plug them into the Agent. ```python async def build_agent() -> ReActAgent: composio_client = Composio( api_key=COMPOSIO_API_KEY, provider=LlamaIndexProvider(), ) session = composio_client.create( user_id=COMPOSIO_USER_ID, toolkits=["parseur"], ) mcp_url = session.mcp.url print(f"Composio MCP URL: {mcp_url}") mcp_client = BasicMCPClient(mcp_url, headers={"x-api-key": COMPOSIO_API_KEY}) mcp_tool_spec = McpToolSpec(client=mcp_client) tools = await mcp_tool_spec.to_tool_list_async() llm = OpenAI(model="gpt-5") description = "An agent that uses Composio Tool Router MCP tools to perform Parseur actions." system_prompt = """ You are a helpful assistant connected to Composio Tool Router. Use the available tools to answer user queries and perform Parseur actions. """ return ReActAgent(tools=tools, llm=llm, description=description, system_prompt=system_prompt, verbose=True) ``` ```typescript async function buildAgent() { console.log(`Initializing Composio client...${COMPOSIO_USER_ID!}...`); console.log(`COMPOSIO_USER_ID: ${COMPOSIO_USER_ID!}...`); const composio = new Composio({ apiKey: COMPOSIO_API_KEY, provider: new LlamaindexProvider(), }); const session = await composio.create( COMPOSIO_USER_ID!, { toolkits: ["parseur"], }, ); const mcpUrl = session.mcp.url; console.log(`Composio Tool Router MCP URL: ${mcpUrl}`); const server = mcp({ url: mcpUrl, clientName: "composio_tool_router_with_llamaindex", requestInit: { headers: { "x-api-key": COMPOSIO_API_KEY!, }, }, // verbose: true, }); const tools = await server.tools(); const llm = openai({ apiKey: OPENAI_API_KEY, model: "gpt-5" }); const agent = createAgent({ name: "composio_tool_router_with_llamaindex", description : "An agent that uses Composio Tool Router MCP tools to perform actions.", systemPrompt: "You are a helpful assistant connected to Composio Tool Router."+ "Use the available tools to answer user queries and perform Parseur actions." , llm, tools, }); return agent; } ``` ### 7. Create an interactive chat loop No description provided. ```python async def chat_loop(agent: ReActAgent) -> None: ctx = Context(agent) print("Type 'quit', 'exit', or Ctrl+C to stop.") while True: try: user_input = input("\nYou: ").strip() except (KeyboardInterrupt, EOFError): print("\nBye!") break if not user_input or user_input.lower() in {"quit", "exit"}: print("Bye!") break try: print("Agent: ", end="", flush=True) handler = agent.run(user_input, ctx=ctx) async for event in handler.stream_events(): # Stream token-by-token from LLM responses if hasattr(event, "delta") and event.delta: print(event.delta, end="", flush=True) # Show tool calls as they happen elif hasattr(event, "tool_name"): print(f"\n[Using tool: {event.tool_name}]", flush=True) # Get final response response = await handler print() # Newline after streaming except KeyboardInterrupt: print("\n[Interrupted]") continue except Exception as e: print(f"\nError: {e}") ``` ```typescript async function chatLoop(agent: ReturnType) { const rl = readline.createInterface({ input, output }); console.log("Type 'quit' or 'exit' to stop."); while (true) { let userInput: string; try { userInput = (await rl.question("\nYou: ")).trim(); } catch { console.log("\nAgent: Bye!"); break; } if (!userInput) { continue; } const lower = userInput.toLowerCase(); if (lower === "quit" || lower === "exit") { console.log("Agent: Bye!"); break; } try { process.stdout.write("Agent: "); const stream = agent.runStream(userInput); let finalResult: any = null; for await (const event of stream) { // The event.data contains the streamed content const data: any = event.data; // Check for streaming delta content if (data?.delta) { process.stdout.write(data.delta); } // Store final result for fallback if (data?.result || data?.message) { finalResult = data; } } // If no streaming happened, show the final result if (finalResult) { const answer = finalResult.result ?? finalResult.message?.content ?? finalResult.message ?? ""; if (answer && typeof answer === "string" && !answer.includes("[object")) { process.stdout.write(answer); } } console.log(); // New line after streaming completes } catch (err: any) { console.error("\nAgent error:", err?.message ?? err); } } rl.close(); } ``` ### 8. Define the main entry point What's happening here: - We're orchestrating the entire application flow - The agent gets built with proper error handling - Then we kick off the interactive chat loop so you can start talking to Parseur ```python async def main() -> None: agent = await build_agent() await chat_loop(agent) if __name__ == "__main__": # Handle Ctrl+C gracefully signal.signal(signal.SIGINT, lambda s, f: (print("\nBye!"), exit(0))) try: asyncio.run(main()) except KeyboardInterrupt: print("\nBye!") ``` ```typescript async function main() { try { const agent = await buildAgent(); await chatLoop(agent); } catch (err) { console.error("Failed to start agent:", err); process.exit(1); } } main(); ``` ### 9. Run the agent When prompted, authenticate and authorise your agent with Parseur, then start asking questions. ```bash python llamaindex_agent.py ``` ```typescript npx ts-node llamaindex-agent.ts ``` ## Complete Code ```python import asyncio import os import signal import dotenv from composio import Composio from composio_llamaindex import LlamaIndexProvider from llama_index.core.agent.workflow import ReActAgent from llama_index.core.workflow import Context from llama_index.llms.openai import OpenAI from llama_index.tools.mcp import BasicMCPClient, McpToolSpec dotenv.load_dotenv() OPENAI_API_KEY = os.getenv("OPENAI_API_KEY") COMPOSIO_API_KEY = os.getenv("COMPOSIO_API_KEY") COMPOSIO_USER_ID = os.getenv("COMPOSIO_USER_ID") if not OPENAI_API_KEY: raise ValueError("OPENAI_API_KEY is not set") if not COMPOSIO_API_KEY: raise ValueError("COMPOSIO_API_KEY is not set") if not COMPOSIO_USER_ID: raise ValueError("COMPOSIO_USER_ID is not set") async def build_agent() -> ReActAgent: composio_client = Composio( api_key=COMPOSIO_API_KEY, provider=LlamaIndexProvider(), ) session = composio_client.create( user_id=COMPOSIO_USER_ID, toolkits=["parseur"], ) mcp_url = session.mcp.url print(f"Composio MCP URL: {mcp_url}") mcp_client = BasicMCPClient(mcp_url, headers={"x-api-key": COMPOSIO_API_KEY}) mcp_tool_spec = McpToolSpec(client=mcp_client) tools = await mcp_tool_spec.to_tool_list_async() llm = OpenAI(model="gpt-5") description = "An agent that uses Composio Tool Router MCP tools to perform Parseur actions." system_prompt = """ You are a helpful assistant connected to Composio Tool Router. Use the available tools to answer user queries and perform Parseur actions. """ return ReActAgent( tools=tools, llm=llm, description=description, system_prompt=system_prompt, verbose=True, ); async def chat_loop(agent: ReActAgent) -> None: ctx = Context(agent) print("Type 'quit', 'exit', or Ctrl+C to stop.") while True: try: user_input = input("\nYou: ").strip() except (KeyboardInterrupt, EOFError): print("\nBye!") break if not user_input or user_input.lower() in {"quit", "exit"}: print("Bye!") break try: print("Agent: ", end="", flush=True) handler = agent.run(user_input, ctx=ctx) async for event in handler.stream_events(): # Stream token-by-token from LLM responses if hasattr(event, "delta") and event.delta: print(event.delta, end="", flush=True) # Show tool calls as they happen elif hasattr(event, "tool_name"): print(f"\n[Using tool: {event.tool_name}]", flush=True) # Get final response response = await handler print() # Newline after streaming except KeyboardInterrupt: print("\n[Interrupted]") continue except Exception as e: print(f"\nError: {e}") async def main() -> None: agent = await build_agent() await chat_loop(agent) if __name__ == "__main__": # Handle Ctrl+C gracefully signal.signal(signal.SIGINT, lambda s, f: (print("\nBye!"), exit(0))) try: asyncio.run(main()) except KeyboardInterrupt: print("\nBye!") ``` ```typescript import "dotenv/config"; import readline from "node:readline/promises"; import { stdin as input, stdout as output } from "node:process"; import { Composio } from "@composio/core"; import { LlamaindexProvider } from "@composio/llamaindex"; import { mcp } from "@llamaindex/tools"; import { agent as createAgent } from "@llamaindex/workflow"; import { openai } from "@llamaindex/openai"; dotenv.config(); const OPENAI_API_KEY = process.env.OPENAI_API_KEY; const COMPOSIO_API_KEY = process.env.COMPOSIO_API_KEY; const COMPOSIO_USER_ID = process.env.COMPOSIO_USER_ID; if (!OPENAI_API_KEY) { throw new Error("OPENAI_API_KEY is not set in the environment"); } if (!COMPOSIO_API_KEY) { throw new Error("COMPOSIO_API_KEY is not set in the environment"); } if (!COMPOSIO_USER_ID) { throw new Error("COMPOSIO_USER_ID is not set in the environment"); } async function buildAgent() { console.log(`Initializing Composio client...${COMPOSIO_USER_ID!}...`); console.log(`COMPOSIO_USER_ID: ${COMPOSIO_USER_ID!}...`); const composio = new Composio({ apiKey: COMPOSIO_API_KEY, provider: new LlamaindexProvider(), }); const session = await composio.create( COMPOSIO_USER_ID!, { toolkits: ["parseur"], }, ); const mcpUrl = session.mcp.url; console.log(`Composio Tool Router MCP URL: ${mcpUrl}`); const server = mcp({ url: mcpUrl, clientName: "composio_tool_router_with_llamaindex", requestInit: { headers: { "x-api-key": COMPOSIO_API_KEY!, }, }, // verbose: true, }); const tools = await server.tools(); const llm = openai({ apiKey: OPENAI_API_KEY, model: "gpt-5" }); const agent = createAgent({ name: "composio_tool_router_with_llamaindex", description: "An agent that uses Composio Tool Router MCP tools to perform actions.", systemPrompt: "You are a helpful assistant connected to Composio Tool Router."+ "Use the available tools to answer user queries and perform Parseur actions." , llm, tools, }); return agent; } async function chatLoop(agent: ReturnType) { const rl = readline.createInterface({ input, output }); console.log("Type 'quit' or 'exit' to stop."); while (true) { let userInput: string; try { userInput = (await rl.question("\nYou: ")).trim(); } catch { console.log("\nAgent: Bye!"); break; } if (!userInput) { continue; } const lower = userInput.toLowerCase(); if (lower === "quit" || lower === "exit") { console.log("Agent: Bye!"); break; } try { process.stdout.write("Agent: "); const stream = agent.runStream(userInput); let finalResult: any = null; for await (const event of stream) { // The event.data contains the streamed content const data: any = event.data; // Check for streaming delta content if (data?.delta) { process.stdout.write(data.delta); } // Store final result for fallback if (data?.result || data?.message) { finalResult = data; } } // If no streaming happened, show the final result if (finalResult) { const answer = finalResult.result ?? finalResult.message?.content ?? finalResult.message ?? ""; if (answer && typeof answer === "string" && !answer.includes("[object")) { process.stdout.write(answer); } } console.log(); // New line after streaming completes } catch (err: any) { console.error("\nAgent error:", err?.message ?? err); } } rl.close(); } async function main() { try { const agent = await buildAgent(); await chatLoop(agent); } catch (err: any) { console.error("Failed to start agent:", err?.message ?? err); process.exit(1); } } main(); ``` ## Conclusion You've successfully connected Parseur to LlamaIndex through Composio's Tool Router MCP layer. Key takeaways: - Tool Router dynamically exposes Parseur tools through an MCP endpoint - LlamaIndex's ReActAgent handles reasoning and orchestration; Composio handles integrations - The agent becomes more capable without increasing prompt size - Async Python provides clean, efficient execution of agent workflows You can easily extend this to other toolkits like Gmail, Notion, Stripe, GitHub, and more by adding them to the toolkits parameter. ## How to build Parseur MCP Agent with another framework - [OpenAI Agents SDK](https://composio.dev/toolkits/parseur/framework/open-ai-agents-sdk) - [Claude Agent SDK](https://composio.dev/toolkits/parseur/framework/claude-agents-sdk) - [Claude Code](https://composio.dev/toolkits/parseur/framework/claude-code) - [Claude Cowork](https://composio.dev/toolkits/parseur/framework/claude-cowork) - [Codex](https://composio.dev/toolkits/parseur/framework/codex) - [OpenClaw](https://composio.dev/toolkits/parseur/framework/openclaw) - [Hermes](https://composio.dev/toolkits/parseur/framework/hermes-agent) - [CLI](https://composio.dev/toolkits/parseur/framework/cli) - [Google ADK](https://composio.dev/toolkits/parseur/framework/google-adk) - [LangChain](https://composio.dev/toolkits/parseur/framework/langchain) - [Vercel AI SDK](https://composio.dev/toolkits/parseur/framework/ai-sdk) - [Mastra AI](https://composio.dev/toolkits/parseur/framework/mastra-ai) - [CrewAI](https://composio.dev/toolkits/parseur/framework/crew-ai) ## Related Toolkits - [Google Drive](https://composio.dev/toolkits/googledrive) - Google Drive is a cloud storage platform for uploading, sharing, and collaborating on files. It's perfect for keeping your documents accessible and organized across devices. - [Google Docs](https://composio.dev/toolkits/googledocs) - Google Docs is a cloud-based word processor that enables document creation and real-time collaboration. Its seamless sharing and version history make team editing and content management a breeze. - [Google Super](https://composio.dev/toolkits/googlesuper) - Google Super is an all-in-one suite combining Gmail, Drive, Calendar, Sheets, Analytics, and more. It gives you a unified platform to manage your digital life, boosting productivity and organization. - [Affinda](https://composio.dev/toolkits/affinda) - Affinda is an AI-powered document processing platform that automates data extraction from resumes, invoices, and more. It streamlines document-heavy workflows by turning files into structured, actionable data. - [Agility cms](https://composio.dev/toolkits/agility_cms) - Agility CMS is a headless content management system for building and managing digital experiences across platforms. It lets teams update content quickly and deliver omnichannel experiences with ease. - [Algodocs](https://composio.dev/toolkits/algodocs) - Algodocs is an AI-powered platform that automates data extraction from business documents. It delivers fast, secure, and accurate processing without templates or manual training. - [Api2pdf](https://composio.dev/toolkits/api2pdf) - Api2Pdf is a REST API for generating PDFs from HTML, URLs, and documents using powerful engines like wkhtmltopdf and Headless Chrome. It streamlines document conversion and automation for developers and businesses. - [Aryn](https://composio.dev/toolkits/aryn) - Aryn is an AI-powered platform for parsing, extracting, and analyzing data from unstructured documents. Use it to automate document processing and unlock actionable insights from your files. - [Boldsign](https://composio.dev/toolkits/boldsign) - Boldsign is a digital eSignature platform for sending, signing, and tracking documents online. Organizations use it to automate agreements and manage legally binding workflows efficiently. - [Boloforms](https://composio.dev/toolkits/boloforms) - BoloForms is an eSignature platform built for small businesses, offering unlimited signatures, templates, and forms. It simplifies digital document signing and team collaboration at a predictable, fixed price. - [Box](https://composio.dev/toolkits/box) - Box is a cloud content management and file sharing platform for businesses. It helps teams securely store, organize, and collaborate on files from anywhere. - [Carbone](https://composio.dev/toolkits/carbone) - Carbone is a blazing-fast report generator that turns JSON data into PDFs, Word docs, spreadsheets, and more using flexible templates. It lets you automate document creation at scale with minimal code. - [Castingwords](https://composio.dev/toolkits/castingwords) - CastingWords is a transcription service specializing in human-powered, accurate transcripts via a simple API. Get seamless audio-to-text conversion for interviews, meetings, podcasts, and more. - [Cloudconvert](https://composio.dev/toolkits/cloudconvert) - CloudConvert is a powerful file conversion service supporting over 200 file formats. It streamlines converting, compressing, and managing documents, media, and more, all in one place. - [Cloudlayer](https://composio.dev/toolkits/cloudlayer) - Cloudlayer is a document and asset generation service for creating PDFs and images via API or SDKs. It lets you automate high-quality doc creation, saving dev time and reducing manual work. - [Cloudpress](https://composio.dev/toolkits/cloudpress) - Cloudpress is a content export tool for Google Docs and Notion. It automates publishing to your favorite Content Management Systems. - [Contentful graphql](https://composio.dev/toolkits/contentful_graphql) - Contentful graphql is a content delivery API that lets you access Contentful data using GraphQL queries. It gives you efficient, flexible ways to fetch and manage structured content for any digital project. - [Conversion tools](https://composio.dev/toolkits/conversion_tools) - Conversion Tools is an online service for converting documents between formats such as PDF, Word, Excel, XML, and CSV. It lets you automate complex document workflows with just a few clicks. - [Convertapi](https://composio.dev/toolkits/convertapi) - ConvertAPI is a robust file conversion service for documents, images, and spreadsheets. It streamlines programmatic format changes and lets developers automate complex workflows with a single API. - [Craftmypdf](https://composio.dev/toolkits/craftmypdf) - CraftMyPDF is a web-based service for designing and generating PDFs with templates and live data. It streamlines document creation by automating personalized PDFs at scale. ## Frequently Asked Questions ### What are the differences in Tool Router MCP and Parseur MCP? With a standalone Parseur MCP server, the agents and LLMs can only access a fixed set of Parseur tools tied to that server. However, with the Composio Tool Router, agents can dynamically load tools from Parseur and many other apps based on the task at hand, all through a single MCP endpoint. ### Can I use Tool Router MCP with LlamaIndex? Yes, you can. LlamaIndex fully supports MCP integration. You get structured tool calling, message history handling, and model orchestration while Tool Router takes care of discovering and serving the right Parseur tools. ### Can I manage the permissions and scopes for Parseur while using Tool Router? Yes, absolutely. You can configure which Parseur scopes and actions are allowed when connecting your account to Composio. You can also bring your own OAuth credentials or API configuration so you keep full control over what the agent can do. ### How safe is my data with Composio Tool Router? All sensitive data such as tokens, keys, and configuration is fully encrypted at rest and in transit. Composio is SOC 2 Type 2 compliant and follows strict security practices so your Parseur data and credentials are handled as safely as possible. --- [See all toolkits](https://composio.dev/toolkits) · [Composio docs](https://docs.composio.dev/llms.txt)