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MCP Integration — Model Context Protocol

The Wenex Platform gateway exposes an MCP (Model Context Protocol) server at GET /mcp. This allows AI agents (Claude, GPT, Ollama-backed agents) to interact with the platform programmatically using the standardized tool-use protocol.

Endpoint: http://localhost:3010/mcp Transport: Streamable HTTP (HTTP/1.1 chunked) Protocol: MCP v1 (JSON-RPC over HTTP)

What is MCP?

MCP is an open protocol that lets AI models communicate with external tools using a structured JSON-RPC interface. The platform acts as an MCP server, exposing tools that agents can call to query and manipulate data.

graph LR
    Agent["AI Agent\n(Claude / GPT / Ollama)"]
    MCP["MCP Client\n(SDK transport)"]
    GW["Gateway /mcp\n:3010"]
    TOOLS["Platform Tools\nauth_verify\nread_documentations\n+ resource tools"]

    Agent --> MCP --> GW --> TOOLS
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Agent Workflow

A typical agent interaction with the platform:

sequenceDiagram
    participant Agent as AI Agent
    participant GW as Gateway /mcp

    Agent->>GW: connect()
    GW-->>Agent: server startup context
    Agent->>GW: listTools()
    GW-->>Agent: [auth_verify, read_documentations, ...]

    Agent->>GW: callTool("auth_verify")
    GW-->>Agent: { sub, scope, exp }

    Agent->>GW: callTool("read_documentations", { uri: "docs://core/resource-specification" })
    GW-->>Agent: service catalog markdown

    loop Resource operations
        Agent->>GW: callTool("find", { resource: "identity/users", filter: { query: {} } })
        GW-->>Agent: [{ id, username, email }, ...]
    end
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