How to Use the Context7 MCP in LlamaIndex

Q: How do I filter tools in LlamaIndex using Context7?

LlamaIndex supports an allowedtools filter. You can restrict the agent to only use the documentation tools while keeping other system functions separate.

Index live library documentation into LlamaIndex knowledge bases with this MCP Server.

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Connect Context7 MCP to LlamaIndex

Create your Vinkius account to connect Context7 to LlamaIndex and route execution through our secure gateway. The platform manages server hosting, runtime updates, and security layers. Configuration requires no manual server provisioning.

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Setup Context7 with LlamaIndex

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Map library versions for LlamaIndex

Use `resolve_library` to turn a library name into a verified path. This ensures your index points to the correct version, preventing stale references. LlamaIndex then ingests this path metadata. It builds a search index that knows exactly where to find the source of truth for your dependencies.

Ground LlamaIndex RAG in live docs

The `query_docs` tool returns current code examples that LlamaIndex adds to your vector store. Your agents then perform semantic searches over the latest library patterns. This creates a queryable knowledge base that updates itself. You stop guessing if the documentation is current and start searching against verified API data.

Unified indexing with Context7

Combine this MCP server with your existing document loaders. LlamaIndex treats the retrieved code examples as first-class objects within your RAG pipeline. It allows for complex reasoning over documentation. The agent can compare past library versions against current ones using the indexed data.

Setup guide

Set up Context7 MCP in LlamaIndex

Prerequisites

Python 3.10+ installed
llama-index-tools-mcp package
Active Vinkius subscription with a valid endpoint token

1

Install dependencies
Run pip install llama-index-tools-mcp llama-index-llms-openai. The MCP tools package provides BasicMCPClient and McpToolSpec.
2

Connect with BasicMCPClient
Point BasicMCPClient to your Vinkius endpoint URL. Replace [YOUR_TOKEN_HERE] with your token from cloud.vinkius.com. Supports SSE and Streamable HTTP transports.
3

Convert to LlamaIndex tools
Call mcp_tool_spec.to_tool_list_async() to convert all Context7 MCP tools into native FunctionTool objects that any LlamaIndex agent can use.
4

Run with any LLM
Create a FunctionAgent with the tools and your preferred LLM. Swap OpenAI for Anthropic, Gemini, or any LlamaIndex-supported provider.

agent.py

from llama_index.tools.mcp import BasicMCPClient, McpToolSpec
from llama_index.core.agent.workflow import FunctionAgent
from llama_index.llms.openai import OpenAI

# Connect to the MCP
mcp_client = BasicMCPClient(
    "https://edge.vinkius.com/[YOUR_TOKEN_HERE]/mcp"
)
mcp_tool_spec = McpToolSpec(client=mcp_client)

# Convert MCP tools to LlamaIndex tools
tools = await mcp_tool_spec.to_tool_list_async()

# Create and run the agent
agent = FunctionAgent(
    tools=tools,
    llm=OpenAI(model="gpt-4o"),
    system_prompt="You have access to Context7 tools.",
)
response = await agent.run("List recent Context7 data")

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Independent Platform Disclaimer: Vinkius is an independent platform and is not affiliated with, endorsed by, sponsored by, verified by, or otherwise authorized by Context7. All third-party trademarks, logos, and brand names are the property of their respective owners. Their use on this website is strictly for informational purposes to identify service compatibility and interoperability.

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Common questions about Context7 MCP in LlamaIndex

Use the BasicMCPClient to connect the server. You then convert the tools into a spec that your FunctionAgent can execute to query documentation.

Yes, you can feed the tool output into your vector index. This allows your agent to perform retrieval-augmented generation on the documentation it just fetched.

You can specify versions using the library ID tools. LlamaIndex will index these specific versions, allowing your agent to answer questions about legacy codebases.

LlamaIndex supports an allowed_tools filter. You can restrict the agent to only use the documentation tools while keeping other system functions separate.

All documentation lookups are ephemeral and scoped to your session. Context7 only handles public library metadata; no proprietary data is ever indexed or stored on our servers.

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