This repository contains a Model Context Protocol (MCP) server with tools that can access the OpenTelemetry traces andmetrics you've sent to Pydantic Logfire.

This MCP server enables LLMs to retrieve your application's telemetry data, analyze distributedtraces, and make use of the results of arbitrary SQL queries executed using the Pydantic Logfire APIs.

• find_exceptions_in_file - Get the details about the 10 most recent exceptions on the file.

  • Arguments:
    • filepath (string) - The path to the file to find exceptions in.
    • age (integer) - Number of minutes to look back, e.g. 30 for last 30 minutes. Maximum allowed value is 7 days.

• arbitrary_query - Run an arbitrary query on the Pydantic Logfire database.

  • Arguments:
    • query (string) - The query to run, as a SQL string.
    • age (integer) - Number of minutes to look back, e.g. 30 for last 30 minutes. Maximum allowed value is 7 days.

• logfire_link - Creates a link to help the user to view the trace in the Logfire UI.

  • Arguments:
    • trace_id (string) - The trace ID to link to.

• schema_reference - The database schema for the Logfire DataFusion database.

The first thing to do is make sureuv is installed, asuv is used to run the MCP server.

For installation instructions, see theuv installation docs.

If you already have an older version ofuv installed, you might need to update it withuv self update.

In order to make requests to the Pydantic Logfire APIs, the Pydantic Logfire MCP server requires a "read token".

You can create one under the "Read Tokens" section of your project settings in Pydantic Logfire:https://logfire.pydantic.dev/-/redirect/latest-project/settings/read-tokens

Once you haveuv installed and have a Pydantic Logfire read token, you can manually run the MCP server usinguvx (which is provided byuv).

You can specify your read token using theLOGFIRE_READ_TOKEN environment variable:

LOGFIRE_READ_TOKEN=YOUR_READ_TOKEN uvx logfire-mcp@latest

You can also setLOGFIRE_READ_TOKEN in a.env file:

LOGFIRE_READ_TOKEN=pylf_v1_us_...

NOTE: for this to work, the MCP server needs to run with the directory containing the.env file in its working directory.

or using the--read-token flag:

uvx logfire-mcp@latest --read-token=YOUR_READ_TOKEN

If you are running Logfire in a self hosted environment, you need to specify the base URL.This can be done using theLOGFIRE_BASE_URL environment variable:

LOGFIRE_BASE_URL=https://logfire.my-company.com uvx logfire-mcp@latest --read-token=YOUR_READ_TOKEN

You can also use the--base-url argument:

uvx logfire-mcp@latest --base-url=https://logfire.my-company.com --read-token=YOUR_READ_TOKEN

Create a.cursor/mcp.json file in your project root:

{"mcpServers": {"logfire": {"command":"uvx","args": ["logfire-mcp@latest","--read-token=YOUR-TOKEN"]    }  }}

The Cursor doesn't accept theenv field, so you need to use the--read-token flag instead.

Run the following command:

claude mcp add logfire -e LOGFIRE_READ_TOKEN=YOUR_TOKEN -- uvx logfire-mcp@latest

Add to your Claude settings:

{"command": ["uvx"],"args": ["logfire-mcp@latest"],"type":"stdio","env": {"LOGFIRE_READ_TOKEN":"YOUR_TOKEN"  }}

Add to your Cline settings incline_mcp_settings.json:

{"mcpServers": {"logfire": {"command":"uvx","args": ["logfire-mcp@latest"],"env": {"LOGFIRE_READ_TOKEN":"YOUR_TOKEN"      },"disabled":false,"autoApprove": []    }  }}

Make sure youenabled MCP support in VS Code.

Create a.vscode/mcp.json file in your project's root directory:

{"servers": {"logfire": {"type":"stdio","command":"uvx",// or the absolute /path/to/uvx"args": ["logfire-mcp@latest"],"env": {"LOGFIRE_READ_TOKEN":"YOUR_TOKEN"      }    }  }}

Create a.zed/settings.json file in your project's root directory:

{"context_servers": {"logfire": {"source":"custom","command":"uvx","args": ["logfire-mcp@latest"],"env": {"LOGFIRE_READ_TOKEN":"YOUR_TOKEN"      },"enabled":true    }  }}

1. Get details about exceptions from traces in a specific file:

{"name":"find_exceptions_in_file","arguments": {"filepath":"app/api.py","age":1440  }}

Response:

[  {"created_at":"2024-03-20T10:30:00Z","message":"Failed to process request","exception_type":"ValueError","exception_message":"Invalid input format","function_name":"process_request","line_number":"42","attributes": {"service.name":"api-service","code.filepath":"app/api.py"    },"trace_id":"1234567890abcdef"  }]

2. Run a custom query on traces:

{"name":"arbitrary_query","arguments": {"query":"SELECT trace_id, message, created_at, attributes->>'service.name' as service FROM records WHERE severity_text = 'ERROR' ORDER BY created_at DESC LIMIT 10","age":1440  }}

1. "What exceptions occurred in traces from the last hour across all services?"
2. "Show me the recent errors in the file 'app/api.py' with their trace context"
3. "How many errors were there in the last 24 hours per service?"
4. "What are the most common exception types in my traces, grouped by service name?"
5. "Get me the OpenTelemetry schema for traces and metrics"
6. "Find all errors from yesterday and show their trace contexts"

1. First, obtain a Pydantic Logfire read token from:https://logfire.pydantic.dev/-/redirect/latest-project/settings/read-tokens

2. Run the MCP server:

   uvx logfire-mcp@latest --read-token=YOUR_TOKEN

3. Configure your preferred client (Cursor, Claude Desktop, or Cline) using the configuration examples above

4. Start using the MCP server to analyze your OpenTelemetry traces and metrics!

We welcome contributions to help improve the Pydantic Logfire MCP server. Whether you want to add new trace analysis tools, enhance metrics querying functionality, or improve documentation, your input is valuable.

For examples of other MCP servers and implementation patterns, see theModel Context Protocol servers repository.

Pydantic Logfire MCP is licensed under the MIT License. This means you are free to use, modify, and distribute the software, subject to the terms and conditions of the MIT License.

Logfire

Bypydantic·113

Provides access to OpenTelemetry traces and metrics through Logfire.