LangChain Agent MCP Server

# Product Requirements Document: LangChain Agent MCP Server | Document Version | 1.0 | | :--- | :--- | | **Author** | Manus AI | | **Date** | November 23, 2025 | | **Project Name** | LangChain Agent MCP Server | | **Status** | Draft | ## 1. Introduction and Goal The primary goal of the **LangChain Agent MCP Server** project is to create a robust, standalone backend service that exposes the advanced reasoning and tool-use capabilities of a LangChain agent to any Model Context Protocol (MCP) compliant client, such as the MCP Messenger application (`slashmcp`) [1]. This server will act as a bridge, wrapping a complex, multi-step LangChain agent as a single, high-level **MCP Tool**. This abstraction allows LLMs within MCP clients to delegate complex tasks to the specialized LangChain agent via a simple, standardized API call. ## 2. Success Metrics The success of this project will be measured by the following criteria: | Metric | Description | Target | | :--- | :--- | :--- | | **MCP Compliance** | Successful registration and invocation by the MCP Messenger client. | 100% pass rate on manifest and invoke tests. | | **Agent Latency** | Time taken for the MCP Server to execute the LangChain agent and return a result. | P95 latency under 5 seconds for a standard 3-step ReAct chain. | | **Stability** | Uptime and error rate of the deployed server. | 99.9% uptime; < 0.1% invocation error rate. | | **Developer Adoption** | Ease of use for developers to define and integrate new LangChain agents. | Clear, comprehensive documentation and a simple setup process. | ## 3. Target Audience * **MCP Messenger Developers:** To integrate the server as a new, powerful slash command or tool. * **LangChain Developers:** To provide a production-ready, scalable deployment target for their LangChain agents. * **End-Users of MCP Messenger:** To gain access to more complex, multi-step reasoning and external tool execution capabilities. ## 4. Features and Requirements ### 4.1. Functional Requirements | ID | Requirement | Description | Priority | | :--- | :--- | :--- | :--- | | **FR1** | **MCP Manifest Endpoint** | The server MUST expose a `/mcp/manifest` endpoint that returns a valid MCP manifest JSON, declaring the wrapped LangChain agent as a single `tool` (e.g., `agent_executor`). | High | | **FR2** | **MCP Invoke Endpoint** | The server MUST expose a `/mcp/invoke` endpoint that accepts a POST request with the MCP invocation payload. | High | | **FR3** | **Agent Execution** | The `/mcp/invoke` endpoint MUST extract the user query from the payload and pass it to the underlying LangChain agent for execution. | High | | **FR4** | **Result Mapping** | The server MUST map the final output of the LangChain agent (the final answer) to the MCP response format. | High | | **FR5** | **Tool Definition** | The server MUST allow for easy configuration of the internal tools the LangChain agent can use (e.g., a `search_web` tool). | Medium | | **FR6** | **Error Handling** | The server MUST catch exceptions during agent execution and return a structured error response via the MCP protocol. | High | ### 4.2. Non-Functional Requirements | ID | Requirement | Description | Priority | | :--- | :--- | :--- | :--- | | **NFR1** | **Scalability** | The server architecture MUST be stateless to allow for horizontal scaling (e.g., running multiple instances behind a load balancer). | High | | **NFR2** | **Security** | The server MUST be deployable behind a firewall and SHOULD support API key or token-based authentication for the `/mcp/invoke` endpoint. | High | | **NFR3** | **Performance** | The server MUST efficiently manage the lifecycle of the LangChain agent to minimize overhead per request. | High | | **NFR4** | **Observability** | The server MUST include logging for all incoming requests, agent steps (if possible), and outgoing responses. | Medium | ## 5. Technical Specification ### 5.1. Technology Stack | Component | Technology | Rationale | | :--- | :--- | :--- | | **Core Framework** | Python 3.11+ | Native language for LangChain and LangGraph. | | **Web Framework** | FastAPI | High performance, modern, and includes automatic OpenAPI/Swagger documentation for the MCP endpoints. | | **Agent Framework** | LangChain / LangGraph [2] | Recommended framework for building production-ready, stateful agents. | | **Deployment** | Docker | Provides a consistent, portable environment for deployment on any cloud platform (e.g., AWS, GCP, Azure). | ### 5.2. Architecture The server will be a simple, single-process web application. 1. **LangChain Agent Initialization:** The LangChain agent (built with LangGraph) and its tools will be initialized once at server startup. 2. **Request Handling:** FastAPI will handle incoming HTTP requests. 3. **`/mcp/manifest`:** Returns a static JSON file. 4. **`/mcp/invoke`:** Calls the pre-initialized `agent_executor.invoke()` method and returns the result. ### 5.3. Repository Structure (Proposed) ``` /langchain-agent-mcp-server ├── Dockerfile ├── README.md ├── requirements.txt ├── src/ │ ├── __init__.py │ ├── main.py # FastAPI application, MCP endpoints │ ├── agent.py # LangChain/LangGraph agent definition and tools │ └── mcp_manifest.json # Static manifest file └── tests/ └── test_mcp_endpoints.py ``` ## 6. Out of Scope (Initial Release) The following items are explicitly out of scope for the initial v1.0 release: * **Dynamic Agent Configuration:** The ability to dynamically change the agent's LLM, prompt, or tools via the MCP invocation payload. The agent will be statically defined in `agent.py`. * **Multi-Agent Systems:** Support for complex multi-agent architectures (e.g., a crew of agents). The initial focus is on a single, powerful agent. * **Streaming Support:** The initial implementation will use a synchronous request/response model. Streaming the agent's thought process back to the client is a future enhancement. * **User-Specific State/Memory:** The agent will be stateless across different user invocations. Session management and persistent memory are v2.0 features. *** ## References [1] mcpmessenger/slashmcp. *GitHub*. https://github.com/mcpmessenger/slashmcp [2] LangGraph. *LangChain Documentation*. https://docs.langchain.com/oss/python/langgraph/ [3] Model Context Protocol. *modelcontextprotocol.io*. https://modelcontextprotocol.io/