
logfire mcp
The Logfire MCP Server is here! :tada:
Repository Info
About This Server
The Logfire MCP Server is here! :tada:
Model Context Protocol (MCP) - This server can be integrated with AI applications to provide additional context and capabilities, enabling enhanced AI interactions and functionality.
Documentation
Pydantic Logfire MCP Server
This repository contains a Model Context Protocol (MCP) server with tools that can access the OpenTelemetry traces and metrics you've sent to Pydantic Logfire.
This MCP server enables LLMs to retrieve your application's telemetry data, analyze distributed traces, and make use of the results of arbitrary SQL queries executed using the Pydantic Logfire APIs.
Available Tools
-
find_exceptions_in_file- Get detailed trace information about exceptions in a specific file- Required arguments:
filepath(string): Path to the file to analyzeage(int): Number of minutes to look back (max 7 days)
- Required arguments:
-
arbitrary_query- Run custom SQL queries on your OpenTelemetry traces and metrics- Required arguments:
query(string): SQL query to executeage(int): Number of minutes to look back (max 7 days)
- Required arguments:
-
get_logfire_records_schema- Get the OpenTelemetry schema to help with custom queries- No required arguments
-
logfire_link- Get a link to the trace in Pydantic Logfire- Required arguments:
trace_id(string): The trace ID to link to
- Required arguments:
Setup
Install uv
The first thing to do is make sure uv is installed, as uv is used to run the MCP server.
For installation instructions, see the uv installation docs.
If you already have an older version of uv installed, you might need to update it with uv self update.
Obtain a Pydantic Logfire read token
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
IMPORTANT
Pydantic Logfire read tokens are project-specific, so you need to create one for the specific project you want to expose to the Pydantic Logfire MCP server.
Manually run the server
Once you have uv installed and have a Pydantic Logfire read token, you can manually run the MCP server using uvx (which is provided by uv).
You can specify your read token using the LOGFIRE_READ_TOKEN environment variable:
LOGFIRE_READ_TOKEN=YOUR_READ_TOKEN uvx logfire-mcp@latest
You can also set LOGFIRE_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
NOTE
If you are using Cursor, Claude Desktop, Cline, or other MCP clients that manage your MCP servers for you, you do NOT need to manually run the server yourself. The next section will show you how to configure these clients to make use of the Pydantic Logfire MCP server.
Base URL
If you are running Logfire in a self hosted environment, you need to specify the base URL.
This can be done using the LOGFIRE_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
Configuration with well-known MCP clients
Configure for Cursor
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 the env field, so you need to use the --read-token flag instead.
Configure for Claude code
Run the following command:
claude mcp add logfire -e LOGFIRE_READ_TOKEN=YOUR_TOKEN -- uvx logfire-mcp@latest
Configure for Claude Desktop
Add to your Claude settings:
{
"command": ["uvx"],
"args": ["logfire-mcp@latest"],
"type": "stdio",
"env": {
"LOGFIRE_READ_TOKEN": "YOUR_TOKEN"
}
}
Configure for Cline
Add to your Cline settings in cline_mcp_settings.json:
{
"mcpServers": {
"logfire": {
"command": "uvx",
"args": ["logfire-mcp@latest"],
"env": {
"LOGFIRE_READ_TOKEN": "YOUR_TOKEN"
},
"disabled": false,
"autoApprove": []
}
}
}
Configure for VS Code
Make sure you enabled 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"
}
}
}
}
Configure for Zed
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
}
}
}
Example Interactions
- 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"
}
]
- 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
}
}
Examples of Questions for Claude
- "What exceptions occurred in traces from the last hour across all services?"
- "Show me the recent errors in the file 'app/api.py' with their trace context"
- "How many errors were there in the last 24 hours per service?"
- "What are the most common exception types in my traces, grouped by service name?"
- "Get me the OpenTelemetry schema for traces and metrics"
- "Find all errors from yesterday and show their trace contexts"
Getting Started
-
First, obtain a Pydantic Logfire read token from: https://logfire.pydantic.dev/-/redirect/latest-project/settings/read-tokens
-
Run the MCP server:
uvx logfire-mcp@latest --read-token=YOUR_TOKEN -
Configure your preferred client (Cursor, Claude Desktop, or Cline) using the configuration examples above
-
Start using the MCP server to analyze your OpenTelemetry traces and metrics!
Contributing
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 the Model Context Protocol servers repository.
License
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.
Quick Start
Clone the repository
git clone https://github.com/pydantic/logfire-mcpInstall dependencies
cd logfire-mcp
npm installFollow the documentation
Check the repository's README.md file for specific installation and usage instructions.
Repository Details
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