observe-instrument-mcp
Server Configuration
Describes the environment variables required to run the server.
| Name | Required | Description | Default |
|---|---|---|---|
| LLM_MODEL | No | Model to use (default: claude-sonnet-4-6) | |
| GROQ_API_KEY | No | Required for Groq models | |
| GEMINI_API_KEY | No | Required for Google Gemini models | |
| OPENAI_API_KEY | No | Required for OpenAI models | |
| ANTHROPIC_API_KEY | No | Required for Anthropic models |
Instructions
Guidance the server publishes about itself, which clients place ahead of the tool catalog so the model reads it before choosing anything.
This server publishes no instructions, or was last inspected before Glama recorded them.
Capabilities
Features and capabilities supported by this server
Protocol revision2025-11-25
| Capability | Details |
|---|---|
| tools | {
"listChanged": false
} |
| prompts | {
"listChanged": false
} |
| resources | {
"subscribe": false,
"listChanged": false
} |
| experimental | {} |
Tools
Functions exposed to the LLM to take actions
| Name | Description |
|---|---|
| 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. |
| check_instrumentationA | 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. |
Prompts
Interactive templates invoked by user choice
| Name | Description |
|---|---|
No prompts | |
Resources
Contextual data attached and managed by the client
| Name | Description |
|---|---|
No resources | |
TDQS
Scored across 2 tools
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.
Both tools follow a consistent verb_noun snake_case pattern: check_instrumentation and instrument_agent. The naming is clear and predictable.
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.
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.