traceAI-mcp

# MCP OpenTelemetry Integration ## Overview This integration provides support for using OpenTelemetry with the MCP framework. It enables tracing and monitoring of applications built with MCP. ## Installation 1. **Install traceAI MCP** ```bash pip install traceAI-mcp traceAI-openai ``` ### Set Environment Variables Set up your environment variables to authenticate with FutureAGI ```python import os os.environ["FI_API_KEY"] = FI_API_KEY os.environ["FI_SECRET_KEY"] = FI_SECRET_KEY os.environ["OPENAI_API_KEY"] = OPENAI_API_KEY ``` ## Quickstart ### Register Tracer Provider Set up the trace provider to establish the observability pipeline. The trace provider: ```python from fi_instrumentation import register from fi_instrumentation.fi_types import ProjectType trace_provider = register( project_type=ProjectType.OBSERVE, project_name="my-mcp-project" ) ``` ### Configure MCP Instrumentation Set up your MCP Instrumentation with built-in observability. ```python from traceai_openai import OpenAIInstrumentor from traceai_mcp import MCPInstrumentor OpenAIInstrumentor().instrument(tracer_provider=trace_provider) MCPInstrumentor().instrument(tracer_provider=tracer_provider) ``` Start your MCP server as usual. TraceAI will automatically trace all MCP requests which will be visible in the FutureAGI platform. ### MCP 1.8.1 dependency compatibility MCP 1.8.1 uses a private Pydantic API that is absent in Pydantic 2.14.2. If you must stay on MCP 1.8.1, pin its compatible Pydantic dependency: ```bash pip install "traceAI-mcp" "mcp==1.8.1" "pydantic==2.11.10" ``` This pin applies only to MCP 1.8.1; do not impose it on newer SDK versions. ### Instrumentation lifecycle `uninstrument()` disables this instrumentor's per-message propagation on already-instrumented open streams as well as on newly opened transports; it does not close sessions or remove wrappers installed by other libraries. Reinstalling re-enables the existing instrumented streams and instruments …