Which integrations are available for this server?

Supports automatic instrumentation of agents built with the CrewAI framework, adding OpenTelemetry tracing. Allows the MCP server to use Google Gemini models for generating instrumentation code. Supports automatic instrumentation of agents built with the LangGraph framework, adding OpenTelemetry tracing. Allows the MCP server to use local LLMs via Ollama for generating instrumentation code with no API key required. Allows the MCP server to use OpenAI's models for generating instrumentation code, and supports instrumenting agents built with the OpenAI SDK. The instrumented agents emit OpenTelemetry-compatible traces, metrics, and logs for observability.

How do I use observe-instrument-mcp?

1. Click on "Deploy Server". 2. Wait a few minutes for the server to deploy. Once ready, it will show a "Started" state. 3. In the chat, type @ followed by the MCP server name and your instructions, e.g., "@observe-instrument-mcp Add observe SDK instrumentation to my_agent.py" That's it! The server will respond to your query, and you can continue using it as needed. Here is a step-by-step guide with screenshots.

observe-instrument-mcp

by alanzha2

Overview Schema Source Related Servers Discussions Admin

Python

Local

observe-instrument-mcp

An MCP server that automatically instruments Python AI agents with the ioa-observe-sdk — adding OpenTelemetry-based tracing, metrics, and logs with zero manual effort.

Works with any MCP-compatible AI coding assistant: Claude Desktop, Cursor, Windsurf, and others.

What it does

Two tools:

instrument_agent — reads a Python agent file, applies full observe SDK instrumentation, writes it back, and returns a summary of changes. Creates a .bak backup before modifying.

check_instrumentation — audits a file for missing instrumentation without modifying it.

Supported frameworks: LlamaIndex, LangGraph, CrewAI, raw OpenAI SDK.

Related MCP server: cursor-otel

Installation

pip install observe-instrument-mcp
# or
uv add observe-instrument-mcp

Requires an API key for your chosen LLM provider. Defaults to Claude (ANTHROPIC_API_KEY). See supported providers below.

Configuration

Claude Desktop

Add to ~/Library/Application Support/Claude/claude_desktop_config.json:

{
  "mcpServers": {
    "observe-instrument": {
      "command": "uvx",
      "args": ["observe-instrument-mcp"],
      "env": {
        "ANTHROPIC_API_KEY": "sk-ant-..."
      }
    }
  }
}

Cursor

Add to .cursor/mcp.json in your project:

{
  "mcpServers": {
    "observe-instrument": {
      "command": "uvx",
      "args": ["observe-instrument-mcp"],
      "env": {
        "ANTHROPIC_API_KEY": "sk-ant-..."
      }
    }
  }
}

Windsurf

Add to ~/.codeium/windsurf/mcp_config.json:

{
  "mcpServers": {
    "observe-instrument": {
      "command": "uvx",
      "args": ["observe-instrument-mcp"],
      "env": {
        "ANTHROPIC_API_KEY": "sk-ant-..."
      }
    }
  }
}

Examples

Ready-to-use uninstrumented agent files are included in the examples/ folder:

examples/
  single-agent/
    openai-sdk-example.py      # OpenAI SDK customer support agent
    langgraph-example.py       # LangGraph currency converter
    llama-index-example.py     # LlamaIndex math agent
    crewai-example.py          # CrewAI research crew
  multi-agent/
    openai-sdk-multi-agent-example.py   # OpenAI SDK orchestrator pipeline
    langgraph-multi-agent-example.py    # LangGraph supervisor pattern
    llama-index-multi-agent-example.py  # LlamaIndex research + writing pipeline
    crewai-multi-agent-example.py       # CrewAI research + publishing crews

Usage

Once configured, ask your AI assistant:

Instrument my agent with the observe SDK: path/to/my_agent.py

Check what observe SDK instrumentation is missing from path/to/my_agent.py

Environment variables

Variable	Description
`LLM_MODEL`	Model to use (default: `claude-sonnet-4-6`). See provider table below.
`ANTHROPIC_API_KEY`	Required for Anthropic models
`OPENAI_API_KEY`	Required for OpenAI models
`GEMINI_API_KEY`	Required for Google Gemini models
`GROQ_API_KEY`	Required for Groq models

Supported providers

Provider	Key variable	`LLM_MODEL` example
Anthropic	`ANTHROPIC_API_KEY`	`claude-sonnet-4-6`
OpenAI	`OPENAI_API_KEY`	`gpt-4o`
Google Gemini	`GEMINI_API_KEY`	`gemini/gemini-2.0-flash`
Groq	`GROQ_API_KEY`	`groq/llama-3.3-70b`
Ollama (local, free)	none	`ollama/llama3.2`

After instrumentation

Install the SDK in your project:

pip install ioa-observe-sdk
# or
uv add ioa-observe-sdk

Start the observability stack (OTel Collector + ClickHouse):

cd path/to/observe/deploy
docker compose up -d

Run your agent:

OPENAI_API_KEY=sk-... OTLP_HTTP_ENDPOINT=http://localhost:4318 python my_agent.py

Query traces:

docker exec -it clickhouse-server clickhouse-client --user admin --password admin

SELECT SpanName, ServiceName, Duration / 1000000. AS ms, Timestamp
FROM otel_traces
ORDER BY Timestamp DESC
LIMIT 20;

Development

git clone https://github.com/alanzha2/observe-instrument-mcp
cd observe-instrument-mcp
pip install -e .

# Test the server locally
mcp dev observe_instrument_mcp/server.py

License

Apache-2.0

Available Tools

2 tools

check_instrumentationA

Read-onlyIdempotent

Audit a Python AI agent file for missing ioa-observe-sdk instrumentation.

Read-only — does not modify the file. Use instrument_agent to apply changes.

Args: file_path: Path to the Python file to audit.

Returns: Audit report: what is present, what is missing, and specific recommendations.

Inputs: file_path (required). Returns: result

instrument_agentA

Read a Python AI agent file, add ioa-observe-sdk instrumentation, and write it back.

Adds Observe.init(), SDK imports, @tool/@agent/@graph/@workflow decorators, and session_start() — covering LlamaIndex, LangGraph, CrewAI, and raw OpenAI SDK agents. Creates a .bak backup before modifying the file.

Args: file_path: Path to the Python file to instrument. app_name: Optional app name for Observe.init(). Inferred from file if omitted.

Returns: Summary of all changes made, the diff, and next steps.

Inputs: file_path (required), app_name. Returns: result

Tool Schema Changelog

Recent tool additions, removals, and schema changes observed during successful MCP inspections.

Loading tool schema changelog…

Deploy Server

Claude Code, inside the Godot 4 editorFlockbay puts an AI agent in the real Godot 4 editor: it writes GDScript, runs your game and fixes what breaks. Free, or bring your own Claude Code or Codex.flockbay.comAd

TDQS

A4.5/5.0

Scored 2026-05-28 01:55 across 2 tools

Disambiguation5/5

The two tools have clearly distinct purposes: one audits for missing instrumentation (read-only), the other applies the instrumentation (modifies the file). There is no overlap or ambiguity.

Naming Consistency5/5

Both tools follow a consistent verb_noun snake_case pattern: check_instrumentation and instrument_agent. The naming is clear and predictable.

Tool Count4/5

With only 2 tools, the server is minimal but appropriately scoped for its specific workflow of auditing and instrumenting Python AI agent files. It is slightly below the typical 3-15 range but still well-focused.

Completeness5/5

The tool set covers the full lifecycle for the stated purpose: check for missing instrumentation and apply it. There is no obvious gap—the backup creation in instrument_agent provides a safety net.

Maintenance

ActivityInactive

ResponsivenessNo recent community issues

Resources

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observe-instrument-mcp

What it does

Installation

Configuration

Claude Desktop

Cursor

Windsurf

Examples

Usage

Environment variables

Supported providers

After instrumentation

Development

License

Available Tools

Tool Schema Changelog

TDQS

Maintenance

Resources

Related MCP Connectors

Related MCP Servers

Observability MCP Server

cursor-otel

otel-mcp

mcp-o11y