# How to integrate Accredible certificates MCP with LlamaIndex

```json
{
  "title": "How to integrate Accredible certificates MCP with LlamaIndex",
  "toolkit": "Accredible certificates",
  "toolkit_slug": "accredible_certificates",
  "framework": "LlamaIndex",
  "framework_slug": "llama-index",
  "url": "https://composio.dev/toolkits/accredible_certificates/framework/llama-index",
  "markdown_url": "https://composio.dev/toolkits/accredible_certificates/framework/llama-index.md",
  "updated_at": "2026-05-06T07:59:08.032Z"
}
```

## Introduction

This guide walks you through connecting Accredible certificates to LlamaIndex using the Composio tool router. By the end, you'll have a working Accredible certificates agent that can bulk create certificates for this course, download pdfs for recent issued credentials, list all available certificate templates through natural language commands.
This guide will help you understand how to give your LlamaIndex agent real control over a Accredible certificates account through Composio's Accredible certificates MCP server.
Before we dive in, let's take a quick look at the key ideas and tools involved.

## Also integrate Accredible certificates with

- [OpenAI Agents SDK](https://composio.dev/toolkits/accredible_certificates/framework/open-ai-agents-sdk)
- [Claude Agent SDK](https://composio.dev/toolkits/accredible_certificates/framework/claude-agents-sdk)
- [Claude Code](https://composio.dev/toolkits/accredible_certificates/framework/claude-code)
- [Claude Cowork](https://composio.dev/toolkits/accredible_certificates/framework/claude-cowork)
- [Codex](https://composio.dev/toolkits/accredible_certificates/framework/codex)
- [OpenClaw](https://composio.dev/toolkits/accredible_certificates/framework/openclaw)
- [Hermes](https://composio.dev/toolkits/accredible_certificates/framework/hermes-agent)
- [CLI](https://composio.dev/toolkits/accredible_certificates/framework/cli)
- [Google ADK](https://composio.dev/toolkits/accredible_certificates/framework/google-adk)
- [LangChain](https://composio.dev/toolkits/accredible_certificates/framework/langchain)
- [Vercel AI SDK](https://composio.dev/toolkits/accredible_certificates/framework/ai-sdk)
- [Mastra AI](https://composio.dev/toolkits/accredible_certificates/framework/mastra-ai)
- [CrewAI](https://composio.dev/toolkits/accredible_certificates/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 Accredible certificates
- Connect LlamaIndex to the Accredible certificates MCP server
- Build a Accredible certificates-powered agent using LlamaIndex
- Interact with Accredible certificates 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 Accredible certificates MCP server, and what's possible with it?

The Accredible certificates MCP server is an implementation of the Model Context Protocol that connects your AI agent and assistants like Claude, Cursor, etc directly to your Accredible certificates account. It provides structured and secure access to your digital credentials platform, so your agent can perform actions like issuing certificates, managing groups, generating PDFs, and organizing templates on your behalf.
- Bulk credential creation and issuance: Let your agent create and issue batches of digital certificates or badges to multiple recipients in one go.
- Automated group and collection management: Effortlessly create, clone, or delete groups and collections to organize recipients and credentials based on your programs or courses.
- Credential evidence and reference handling: Add or remove evidence items or references to credentials, supporting richer documentation and verification for each certificate.
- PDF certificate generation and export: Quickly generate and download PDF copies of credentials, individually or in bulk, for easy offline distribution or archiving.
- Template listing and selection: Retrieve and browse all available certificate templates, so your agent can help you pick or preview designs for new credentials.

## Supported Tools

| Tool slug | Name | Description |
|---|---|---|
| `ACCREDIBLE_CERTIFICATES_BULK_CREATE_CREDENTIALS_V2` | Bulk Create Credentials (V2) | Tool to bulk create credentials. use when batching up to 30 credentials in one call; supports multi-status (207) responses. |
| `ACCREDIBLE_CERTIFICATES_CLONE_GROUP` | Clone Group | Tool to clone an existing group. use after confirming the source group exists and you need a copy with optional overrides. |
| `ACCREDIBLE_CERTIFICATES_CREATE_COLLECTION` | Create Collection | Tool to create a new collection. use when you need a curated set of groups. |
| `ACCREDIBLE_CERTIFICATES_CREATE_EVIDENCE_ITEM` | Create Evidence Item | Tool to create a new evidence item for a credential. use after confirming credential id. |
| `ACCREDIBLE_CERTIFICATES_CREATE_GROUP` | Create Group | Tool to create a new group. use after gathering all group details. |
| `ACCREDIBLE_CERTIFICATES_DELETE_CREDENTIAL` | Delete Credential | Tool to delete a credential. use after confirming you want to permanently remove an existing credential. executes delete on /credentials/{credential id} endpoint and returns status code. |
| `ACCREDIBLE_CERTIFICATES_DELETE_GROUP` | Delete Group | Tool to delete a group. use after confirming no credentials remain and when you need to permanently remove the group. |
| `ACCREDIBLE_CERTIFICATES_DELETE_REFERENCE` | Delete Reference | Tool to delete a specific reference by id. use after confirming both credential id and reference id. example: "delete reference 1234 from credential 'abc123'." |
| `ACCREDIBLE_CERTIFICATES_GENERATE_PD_FS_FOR_CREDENTIALS` | Generate PDFs for Credentials | Tool to generate pdfs for multiple credentials. use when you need to batch-download a zip archive of certificate pdfs for a list of published credential ids. example: "generate pdfs for credentials [10000005, 10272642]". |
| `ACCREDIBLE_CERTIFICATES_LIST_TEMPLATES` | List Templates | Tool to retrieve a list of all templates. use after authentication to fetch paginated certificate templates. |
| `ACCREDIBLE_CERTIFICATES_SEARCH_COLLECTIONS` | Search Collections | Tool to search for collections. use when you need to filter collections by ids, name, or public flag and paginate through results. e.g., "search for public collections named 'abc' on page 2." |
| `ACCREDIBLE_CERTIFICATES_UPDATE_GROUP` | Update Group | Tool to update an existing group. use when you need to modify group details after fetching its current data. |
| `ACCREDIBLE_CERTIFICATES_UPDATE_REFERENCE` | Update Reference | Tool to update a reference by id. use when you need to modify a reference's details for a credential. use after retrieving the reference id to change comments or relationship. |
| `ACCREDIBLE_CERTIFICATES_VIEW_ALL_SKILL_CATEGORIES` | View All Skill Categories | Tool to retrieve all skill categories. use when you need to list all available skill categories (e.g., to link them to groups). |

## Supported Triggers

None listed.

## Creating MCP Server - Stand-alone vs Composio SDK

The Accredible certificates MCP server is an implementation of the Model Context Protocol that connects your AI agent to Accredible certificates. It provides structured and secure access so your agent can perform Accredible certificates 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 Accredible certificates account and project
- Basic familiarity with async Python/Typescript

### 1. Getting API Keys for OpenAI, Composio, and Accredible certificates

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 Accredible certificates 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, accredible certificates)
- 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 Accredible certificates 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=["accredible_certificates"],
    )

    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 Accredible certificates actions."
    system_prompt = """
    You are a helpful assistant connected to Composio Tool Router.
    Use the available tools to answer user queries and perform Accredible certificates 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: ["accredible_certificates"],
    },
  );

  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 Accredible certificates 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<typeof createAgent>) {
  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 Accredible certificates
```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 Accredible certificates, 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=["accredible_certificates"],
    )

    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 Accredible certificates actions."
    system_prompt = """
    You are a helpful assistant connected to Composio Tool Router.
    Use the available tools to answer user queries and perform Accredible certificates 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: ["accredible_certificates"],
    },
  );

  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 Accredible certificates actions." ,
    llm,
    tools,
  });

  return agent;
}

async function chatLoop(agent: ReturnType<typeof createAgent>) {
  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 Accredible certificates to LlamaIndex through Composio's Tool Router MCP layer.
Key takeaways:
- Tool Router dynamically exposes Accredible certificates 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 Accredible certificates MCP Agent with another framework

- [OpenAI Agents SDK](https://composio.dev/toolkits/accredible_certificates/framework/open-ai-agents-sdk)
- [Claude Agent SDK](https://composio.dev/toolkits/accredible_certificates/framework/claude-agents-sdk)
- [Claude Code](https://composio.dev/toolkits/accredible_certificates/framework/claude-code)
- [Claude Cowork](https://composio.dev/toolkits/accredible_certificates/framework/claude-cowork)
- [Codex](https://composio.dev/toolkits/accredible_certificates/framework/codex)
- [OpenClaw](https://composio.dev/toolkits/accredible_certificates/framework/openclaw)
- [Hermes](https://composio.dev/toolkits/accredible_certificates/framework/hermes-agent)
- [CLI](https://composio.dev/toolkits/accredible_certificates/framework/cli)
- [Google ADK](https://composio.dev/toolkits/accredible_certificates/framework/google-adk)
- [LangChain](https://composio.dev/toolkits/accredible_certificates/framework/langchain)
- [Vercel AI SDK](https://composio.dev/toolkits/accredible_certificates/framework/ai-sdk)
- [Mastra AI](https://composio.dev/toolkits/accredible_certificates/framework/mastra-ai)
- [CrewAI](https://composio.dev/toolkits/accredible_certificates/framework/crew-ai)

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## Frequently Asked Questions

### What are the differences in Tool Router MCP and Accredible certificates MCP?

With a standalone Accredible certificates MCP server, the agents and LLMs can only access a fixed set of Accredible certificates tools tied to that server. However, with the Composio Tool Router, agents can dynamically load tools from Accredible certificates 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 Accredible certificates tools.

### Can I manage the permissions and scopes for Accredible certificates while using Tool Router?

Yes, absolutely. You can configure which Accredible certificates 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 Accredible certificates data and credentials are handled as safely as possible.

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[See all toolkits](https://composio.dev/toolkits) · [Composio docs](https://docs.composio.dev/llms.txt)