# How to integrate Spondyr MCP with LangChain ```json { "title": "How to integrate Spondyr MCP with LangChain", "toolkit": "Spondyr", "toolkit_slug": "spondyr", "framework": "LangChain", "framework_slug": "langchain", "url": "https://composio.dev/toolkits/spondyr/framework/langchain", "markdown_url": "https://composio.dev/toolkits/spondyr/framework/langchain.md", "updated_at": "2026-05-12T10:26:53.357Z" } ``` ## Introduction This guide walks you through connecting Spondyr to LangChain using the Composio tool router. By the end, you'll have a working Spondyr agent that can list all transaction types in spondyr, create condition rules for refund events, update event type name for shipped orders through natural language commands. This guide will help you understand how to give your LangChain agent real control over a Spondyr account through Composio's Spondyr MCP server. Before we dive in, let's take a quick look at the key ideas and tools involved. ## Also integrate Spondyr with - [OpenAI Agents SDK](https://composio.dev/toolkits/spondyr/framework/open-ai-agents-sdk) - [Claude Agent SDK](https://composio.dev/toolkits/spondyr/framework/claude-agents-sdk) - [Claude Code](https://composio.dev/toolkits/spondyr/framework/claude-code) - [Claude Cowork](https://composio.dev/toolkits/spondyr/framework/claude-cowork) - [Codex](https://composio.dev/toolkits/spondyr/framework/codex) - [OpenClaw](https://composio.dev/toolkits/spondyr/framework/openclaw) - [Hermes](https://composio.dev/toolkits/spondyr/framework/hermes-agent) - [CLI](https://composio.dev/toolkits/spondyr/framework/cli) - [Google ADK](https://composio.dev/toolkits/spondyr/framework/google-adk) - [Vercel AI SDK](https://composio.dev/toolkits/spondyr/framework/ai-sdk) - [Mastra AI](https://composio.dev/toolkits/spondyr/framework/mastra-ai) - [LlamaIndex](https://composio.dev/toolkits/spondyr/framework/llama-index) - [CrewAI](https://composio.dev/toolkits/spondyr/framework/crew-ai) ## TL;DR Here's what you'll learn: - Get and set up your OpenAI and Composio API keys - Connect your Spondyr project to Composio - Create a Tool Router MCP session for Spondyr - Initialize an MCP client and retrieve Spondyr tools - Build a LangChain agent that can interact with Spondyr - Set up an interactive chat interface for testing ## What is LangChain? LangChain is a framework for developing applications powered by language models. It provides tools and abstractions for building agents that can reason, use tools, and maintain conversation context. Key features include: - Agent Framework: Build agents that can use tools and make decisions - MCP Integration: Connect to external services through Model Context Protocol adapters - Memory Management: Maintain conversation history across interactions - Multi-Provider Support: Works with OpenAI, Anthropic, and other LLM providers ## What is the Spondyr MCP server, and what's possible with it? The Spondyr MCP server is an implementation of the Model Context Protocol that connects your AI agent and assistants like Claude, Cursor, etc directly to your Spondyr account. It provides structured and secure access to your Spondyr templates, transaction types, events, and correspondence workflows, so your agent can perform actions like managing conditions, handling recipients, orchestrating correspondence delivery, and monitoring status updates for your business communications. - Comprehensive transaction type management: Quickly create, list, or update transaction types—making it easy for your agent to adapt Spondyr to your evolving business data needs. - Rule-based template selection: Define and manage conditions that control which templates are used for different transaction scenarios, ensuring your communications are always personalized and relevant. - Automated correspondence delivery and tracking: Have your agent trigger the delivery of generated correspondence and fetch real-time status updates, so you always know when and how your messages are sent. - Dynamic event and recipient handling: List, retrieve, update, or delete event types and recipient information to keep your communication flows flexible and up-to-date. - Seamless integration and configuration management: Effortlessly connect, configure, and synchronize your Spondyr settings and workflows—without manual intervention or custom code. ## Supported Tools | Tool slug | Name | Description | |---|---|---| | `SPONDYR_CONDITIONS_LIST` | List Conditions | Tool to list all conditions for a transaction type. Use when you need to discover existing condition rules before creating templates or generating correspondence. Conditions define criteria for selecting specific templates based on transaction data. | | `SPONDYR_CREATE_CONDITION` | Create Condition | Create a condition rule for template selection in Spondyr. Conditions define matching criteria on transaction data fields that determine which document template to use. For example, create a condition on an 'OrderStatus' field to trigger different email templates for 'Pending' vs 'Shipped' orders. | | `SPONDYR_CREATE_TRANSACTION_TYPE` | Create Transaction Type | Tool to create a new transaction type. Use after defining the JSON schema for your data to register it in Spondyr. | | `SPONDYR_DELIVER_SPONDYR` | Deliver Spondyr correspondence | Trigger delivery of previously generated correspondence to recipients. Use this action after generating correspondence (via POST /Spondyr with IsGenerateOnly=true) to actually deliver the documents via email, fax, mail, or text message. The ReferenceID from the generate request is required to identify which correspondence to deliver. | | `SPONDYR_EVENT_TYPE_UPDATE` | Update Event Type | Tool to update an existing event type name within a transaction type. Use when you need to rename an Event Type. Example: Rename the 'OrderShipped' event to 'OrderDelivered' within the 'CustomerOrders' transaction type. Note: This only changes the event type's name - it does not move the event to a different transaction type. | | `SPONDYR_GET_EVENT_TYPES` | List Event Types for Transaction Type | Retrieves all event types associated with a specific transaction type in Spondyr. Event types define the kinds of events that can occur for a transaction type (e.g., "Created", "Updated", "Cancelled" events for an "Order" transaction type). Use this action after retrieving transaction types to discover what event types are available for a given transaction type. This is essential for understanding the event-driven workflows and setting up event-based automation in Spondyr. Returns an empty list if the transaction type exists but has no event types configured. | | `SPONDYR_GET_SPONDYR_STATUS` | Get Spondyr Status | Tool to retrieve the status of a previously generated correspondence. Use after generating correspondence to check its processing and delivery status. | | `SPONDYR_GET_TRANSACTION_TYPES` | Get Transaction Types | Tool to retrieve a list of available transaction types. Use after authentication to discover data schemas. | | `SPONDYR_RECIPIENT_DELETE` | Delete Recipient | Deletes a recipient configuration from a transaction type in Spondyr. Recipients are configured delivery endpoints (email addresses, fax numbers, physical addresses) that determine where correspondence will be sent when a transaction is processed. This action permanently removes a recipient configuration from the specified transaction type. Before deletion, use the 'List Recipients' action to verify the recipient name and transaction type. After successful deletion, the recipient will no longer be available for correspondence delivery. | | `SPONDYR_RECIPIENT_GET` | Get Recipient | Tool to retrieve details of a specific recipient. Use when you need to fetch recipient configuration for a given transaction type. Example: "Retrieve recipient 'Customer' for transaction type 'OrderPlaced'." | | `SPONDYR_RECIPIENTS_LIST` | List Recipients | Tool to list all recipients for a transaction type. Use when you need to discover or verify all configured recipients before sending or managing correspondence. | | `SPONDYR_SEARCH_FILTER_CREATE` | Create Search Filter | Create a new search filter for a transaction type in Spondyr. Search filters enable you to define searchable fields within your transaction data. Once created, these filters allow you to quickly search and retrieve specific transactions based on field values (e.g., search by OrderID, CustomerName, InvoiceNumber). Use this tool when you need to make a specific field searchable within a transaction type. | | `SPONDYR_SEARCH_FILTER_DELETE` | Delete Search Filter | Deletes a specific search filter from the Spondyr system. Use this when you need to remove a search filter that is no longer needed. Both the filter name and transaction type must exactly match the values used when the filter was created. If the filter does not exist, the API will return an error. | | `SPONDYR_SEARCH_FILTER_GET` | Get Search Filter | Retrieves details of a specific search filter in Spondyr by name and transaction type. Returns the filter's name, tag value, and associated transaction type. Use this when you need to look up an existing search filter's configuration, verify its tag format, or confirm which transaction type it belongs to before using it for correspondence searches. | | `SPONDYR_SEARCH_FILTERS_LIST` | List Search Filters | Tool to list all search filters for a transaction type. Use when you need to discover available filters before searching correspondence. | | `SPONDYR_SEARCH_SPONDYRS` | Search Correspondence | Search for generated correspondence (spondyrs) by multiple criteria including batch ID, event type, and custom search filters. Returns paginated results with delivery status, recipient information, and URIs to access generated documents. Use this to find and retrieve previously generated correspondence. | | `SPONDYR_SSO_STUB` | Create Spondyr SSO stub | Tool to create a one-time SSO user stub in Spondyr. Use after application authentication to generate a temporary SSO token for embedding or redirecting users. | | `SPONDYR_TEMPLATE_GET` | Get Template | Retrieve detailed configuration for a specific correspondence template. Returns template content reference ID, event type, recipients, delivery methods, conditions, and search filters. Use this action when you need to: - Inspect template settings and configuration - View recipient delivery methods (Email, Mail, Text, DocuSign, Fax, Destination) - Review template selection conditions and search filters - Get the template content reference ID for correspondence generation Prerequisites: Use 'Get Transaction Types' to discover transaction types, then 'List Templates' to find available template names. Example: Retrieve template 'OrderConfirmationEmail' for transaction type 'CustomerOrder'. | | `SPONDYR_TEMPLATES_LIST` | List Templates | List all templates configured for a transaction type. Use this to discover available templates before generating correspondence or to audit template configurations. Returns template metadata including name, event type, content type, recipients, conditions, and search filters. Use Get Template action to retrieve full template content and detailed configuration. | | `SPONDYR_TRANSACTION_TYPE_GET` | Get Transaction Type | Tool to retrieve details of a specific transaction type. Use when inspecting a transaction type schema. Returns the schema definition including JSON structure and CSV field mappings. Example: "Get transaction type 'CustomerOrder' to view its JSON schema and available fields." | | `SPONDYR_TRANSACTION_TYPE_UPDATE` | Update Transaction Type | Updates an existing transaction type's name and/or JSON schema in Spondyr. Use this tool to: - Modify the JSON schema/template of a transaction type to add, remove, or change data fields - Rename an existing transaction type - Update sample data values in the template Prerequisites: The transaction type must already exist. Use 'Get Transaction Types' to list available types or 'Get Transaction Type' to retrieve the current schema before updating. Example: Update the 'OrderPlaced' transaction type with a new JSON schema that includes customer address fields. | ## Supported Triggers None listed. ## Creating MCP Server - Stand-alone vs Composio SDK The Spondyr MCP server is an implementation of the Model Context Protocol that connects your AI agent to Spondyr. It provides structured and secure access so your agent can perform Spondyr 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 No description provided. ### 1. Getting API Keys for OpenAI and Composio OpenAI API Key - Go to the [OpenAI dashboard](https://platform.openai.com/settings/organization/api-keys) and create an API key. You'll need credits to use the models, or you can connect to another model provider. - Keep the API key safe. Composio API Key - Log in to the [Composio dashboard](https://dashboard.composio.dev?utm_source=toolkits&utm_medium=framework_docs). - Navigate to your API settings and generate a new API key. - Store this key securely as you'll need it for authentication. ### 2. Install dependencies No description provided. ```python pip install composio-langchain langchain-mcp-adapters langchain python-dotenv ``` ```typescript npm install @composio/langchain @langchain/core @langchain/openai @langchain/mcp-adapters dotenv ``` ### 3. Set up environment variables Create a .env file in your project root. What's happening: - COMPOSIO_API_KEY authenticates your requests to Composio's API - COMPOSIO_USER_ID identifies the user for session management - OPENAI_API_KEY enables access to OpenAI's language models ```bash COMPOSIO_API_KEY=your_composio_api_key_here COMPOSIO_USER_ID=your_composio_user_id_here OPENAI_API_KEY=your_openai_api_key_here ``` ### 4. Import dependencies No description provided. ```python from langchain_mcp_adapters.client import MultiServerMCPClient from langchain.agents import create_agent from dotenv import load_dotenv from composio import Composio import asyncio import os load_dotenv() ``` ```typescript import { Composio } from '@composio/core'; import { LangchainProvider } from '@composio/langchain'; import { MultiServerMCPClient } from "@langchain/mcp-adapters"; import { createAgent } from "langchain"; import * as readline from 'readline'; import 'dotenv/config'; dotenv.config(); ``` ### 5. Initialize Composio client What's happening: - We're loading the COMPOSIO_API_KEY from environment variables and validating it exists - Creating a Composio instance that will manage our connection to Spondyr tools - Validating that COMPOSIO_USER_ID is also set before proceeding ```python async def main(): composio = Composio(api_key=os.getenv("COMPOSIO_API_KEY")) if not os.getenv("COMPOSIO_API_KEY"): raise ValueError("COMPOSIO_API_KEY is not set") if not os.getenv("COMPOSIO_USER_ID"): raise ValueError("COMPOSIO_USER_ID is not set") ``` ```typescript const composioApiKey = process.env.COMPOSIO_API_KEY; const userId = process.env.COMPOSIO_USER_ID; if (!composioApiKey) throw new Error('COMPOSIO_API_KEY is not set'); if (!userId) throw new Error('COMPOSIO_USER_ID is not set'); async function main() { const composio = new Composio({ apiKey: composioApiKey as string, provider: new LangchainProvider() }); ``` ### 6. Create a Tool Router session What's happening: - We're creating a Tool Router session that gives your agent access to Spondyr tools - The create method takes the user ID and specifies which toolkits should be available - The returned session.mcp.url is the MCP server URL that your agent will use - This approach allows the agent to dynamically load and use Spondyr tools as needed ```python # Create Tool Router session for Spondyr session = composio.create( user_id=os.getenv("COMPOSIO_USER_ID"), toolkits=['spondyr'] ) url = session.mcp.url ``` ```typescript const session = await composio.create( userId as string, { toolkits: ['spondyr'] } ); const url = session.mcp.url; ``` ### 7. Configure the agent with the MCP URL No description provided. ```python client = MultiServerMCPClient({ "spondyr-agent": { "transport": "streamable_http", "url": session.mcp.url, "headers": { "x-api-key": os.getenv("COMPOSIO_API_KEY") } } }) tools = await client.get_tools() agent = create_agent("gpt-5", tools) ``` ```typescript const client = new MultiServerMCPClient({ "spondyr-agent": { transport: "http", url: url, headers: { "x-api-key": process.env.COMPOSIO_API_KEY } } }); const tools = await client.getTools(); const agent = createAgent({ model: "gpt-5", tools }); ``` ### 8. Set up interactive chat interface No description provided. ```python conversation_history = [] print("Chat started! Type 'exit' or 'quit' to end the conversation.\n") print("Ask any Spondyr related question or task to the agent.\n") while True: user_input = input("You: ").strip() if user_input.lower() in ['exit', 'quit', 'bye']: print("\nGoodbye!") break if not user_input: continue conversation_history.append({"role": "user", "content": user_input}) print("\nAgent is thinking...\n") response = await agent.ainvoke({"messages": conversation_history}) conversation_history = response['messages'] final_response = response['messages'][-1].content print(f"Agent: {final_response}\n") ``` ```typescript let conversationHistory: any[] = []; console.log("Chat started! Type 'exit' or 'quit' to end the conversation.\n"); console.log("Ask any Spondyr related question or task to the agent.\n"); const rl = readline.createInterface({ input: process.stdin, output: process.stdout, prompt: 'You: ' }); rl.prompt(); rl.on('line', async (userInput: string) => { const trimmedInput = userInput.trim(); if (['exit', 'quit', 'bye'].includes(trimmedInput.toLowerCase())) { console.log("\nGoodbye!"); rl.close(); process.exit(0); } if (!trimmedInput) { rl.prompt(); return; } conversationHistory.push({ role: "user", content: trimmedInput }); console.log("\nAgent is thinking...\n"); const response = await agent.invoke({ messages: conversationHistory }); conversationHistory = response.messages; const finalResponse = response.messages[response.messages.length - 1]?.content; console.log(`Agent: ${finalResponse}\n`); rl.prompt(); }); rl.on('close', () => { console.log('\n👋 Session ended.'); process.exit(0); }); ``` ### 9. Run the application No description provided. ```python if __name__ == "__main__": asyncio.run(main()) ``` ```typescript main().catch((err) => { console.error('Fatal error:', err); process.exit(1); }); ``` ## Complete Code ```python from langchain_mcp_adapters.client import MultiServerMCPClient from langchain.agents import create_agent from dotenv import load_dotenv from composio import Composio import asyncio import os load_dotenv() async def main(): composio = Composio(api_key=os.getenv("COMPOSIO_API_KEY")) if not os.getenv("COMPOSIO_API_KEY"): raise ValueError("COMPOSIO_API_KEY is not set") if not os.getenv("COMPOSIO_USER_ID"): raise ValueError("COMPOSIO_USER_ID is not set") session = composio.create( user_id=os.getenv("COMPOSIO_USER_ID"), toolkits=['spondyr'] ) url = session.mcp.url client = MultiServerMCPClient({ "spondyr-agent": { "transport": "streamable_http", "url": url, "headers": { "x-api-key": os.getenv("COMPOSIO_API_KEY") } } }) tools = await client.get_tools() agent = create_agent("gpt-5", tools) conversation_history = [] print("Chat started! Type 'exit' or 'quit' to end the conversation.\n") print("Ask any Spondyr related question or task to the agent.\n") while True: user_input = input("You: ").strip() if user_input.lower() in ['exit', 'quit', 'bye']: print("\nGoodbye!") break if not user_input: continue conversation_history.append({"role": "user", "content": user_input}) print("\nAgent is thinking...\n") response = await agent.ainvoke({"messages": conversation_history}) conversation_history = response['messages'] final_response = response['messages'][-1].content print(f"Agent: {final_response}\n") if __name__ == "__main__": asyncio.run(main()) ``` ```typescript import { Composio } from '@composio/core'; import { LangchainProvider } from '@composio/langchain'; import { MultiServerMCPClient } from "@langchain/mcp-adapters"; import { createAgent } from "langchain"; import * as readline from 'readline'; import 'dotenv/config'; const composioApiKey = process.env.COMPOSIO_API_KEY; const userId = process.env.COMPOSIO_USER_ID; if (!composioApiKey) throw new Error('COMPOSIO_API_KEY is not set'); if (!userId) throw new Error('COMPOSIO_USER_ID is not set'); async function main() { const composio = new Composio({ apiKey: composioApiKey as string, provider: new LangchainProvider() }); const session = await composio.create( userId as string, { toolkits: ['spondyr'] } ); const url = session.mcp.url; const client = new MultiServerMCPClient({ "spondyr-agent": { transport: "http", url: url, headers: { "x-api-key": process.env.COMPOSIO_API_KEY } } }); const tools = await client.getTools(); const agent = createAgent({ model: "gpt-5", tools }); let conversationHistory: any[] = []; console.log("Chat started! Type 'exit' or 'quit' to end the conversation.\n"); console.log("Ask any Spondyr related question or task to the agent.\n"); const rl = readline.createInterface({ input: process.stdin, output: process.stdout, prompt: 'You: ' }); rl.prompt(); rl.on('line', async (userInput: string) => { const trimmedInput = userInput.trim(); if (['exit', 'quit', 'bye'].includes(trimmedInput.toLowerCase())) { console.log("\nGoodbye!"); rl.close(); process.exit(0); } if (!trimmedInput) { rl.prompt(); return; } conversationHistory.push({ role: "user", content: trimmedInput }); console.log("\nAgent is thinking...\n"); const response = await agent.invoke({ messages: conversationHistory }); conversationHistory = response.messages; const finalResponse = response.messages[response.messages.length - 1]?.content; console.log(`Agent: ${finalResponse}\n`); rl.prompt(); }); rl.on('close', () => { console.log('\nSession ended.'); process.exit(0); }); } main().catch((err) => { console.error('Fatal error:', err); process.exit(1); }); ``` ## Conclusion You've successfully built a LangChain agent that can interact with Spondyr through Composio's Tool Router. Key features of this implementation: - Dynamic tool loading through Composio's Tool Router - Conversation history maintenance for context-aware responses - Async Python provides clean, efficient execution of agent workflows You can extend this further by adding error handling, implementing specific business logic, or integrating additional Composio toolkits to create multi-app workflows. ## How to build Spondyr MCP Agent with another framework - [OpenAI Agents SDK](https://composio.dev/toolkits/spondyr/framework/open-ai-agents-sdk) - [Claude Agent SDK](https://composio.dev/toolkits/spondyr/framework/claude-agents-sdk) - [Claude Code](https://composio.dev/toolkits/spondyr/framework/claude-code) - [Claude Cowork](https://composio.dev/toolkits/spondyr/framework/claude-cowork) - [Codex](https://composio.dev/toolkits/spondyr/framework/codex) - [OpenClaw](https://composio.dev/toolkits/spondyr/framework/openclaw) - [Hermes](https://composio.dev/toolkits/spondyr/framework/hermes-agent) - [CLI](https://composio.dev/toolkits/spondyr/framework/cli) - [Google ADK](https://composio.dev/toolkits/spondyr/framework/google-adk) - [Vercel AI SDK](https://composio.dev/toolkits/spondyr/framework/ai-sdk) - [Mastra AI](https://composio.dev/toolkits/spondyr/framework/mastra-ai) - [LlamaIndex](https://composio.dev/toolkits/spondyr/framework/llama-index) - [CrewAI](https://composio.dev/toolkits/spondyr/framework/crew-ai) ## Related Toolkits - [Apilio](https://composio.dev/toolkits/apilio) - Apilio is a home automation platform that lets you connect and control smart devices from different brands. 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It streamlines repetitive processes so your business runs smoother, faster, and with fewer manual steps. - [Maintainx](https://composio.dev/toolkits/maintainx) - Maintainx is a cloud-based CMMS for centralizing maintenance data, communication, and workflows. It helps organizations streamline maintenance operations and improve team coordination. - [Make](https://composio.dev/toolkits/make) - Make is an automation platform that connects your favorite apps and services. Build powerful, custom workflows without writing code. - [Ntfy](https://composio.dev/toolkits/ntfy) - Ntfy is a notification service to send push messages to phones or desktops. Instantly deliver alerts and updates to users, devices, or teams. ## Frequently Asked Questions ### What are the differences in Tool Router MCP and Spondyr MCP? With a standalone Spondyr MCP server, the agents and LLMs can only access a fixed set of Spondyr tools tied to that server. However, with the Composio Tool Router, agents can dynamically load tools from Spondyr and many other apps based on the task at hand, all through a single MCP endpoint. ### Can I use Tool Router MCP with LangChain? Yes, you can. LangChain 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 Spondyr tools. ### Can I manage the permissions and scopes for Spondyr while using Tool Router? Yes, absolutely. You can configure which Spondyr 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 Spondyr data and credentials are handled as safely as possible. --- [See all toolkits](https://composio.dev/toolkits) · [Composio docs](https://docs.composio.dev/llms.txt)