Integrates with Logfire, a Pydantic service, to retrieve and analyze application telemetry data through the Logfire APIs using read tokens from the Logfire project settings.
A Model Context Protocol server that enables LLMs to retrieve and analyze OpenTelemetry traces and metrics from Logfire, supporting exception tracking and custom SQL queries against telemetry data.
4
162
MIT
Why this server?
Uses Pydantic for configuration validation and data modeling in SignNow API interactions
A FastMCP server that provides real-time weather data from KNMI weather stations, allowing users to access temperature, humidity, wind speed, and other weather metrics for any location in the Netherlands through natural language queries.
4
4
MIT
Why this server?
Uses Pydantic models from the SDK for structured output validation and data modeling
Enables searching and retrieving content from Grokipedia, including article content, citations, related pages, and section extraction with built-in research workflows.
7
7
MIT
Why this server?
Provides a preset for Pydantic projects, automatically detecting Pydantic and generating configuration to obfuscate Pydantic models while preserving field validators and serialization methods.
Model Context Protocol server for pyobfus — the Python obfuscator. Lets Claude Desktop, Claude Code, Cursor, Windsurf, and Zed call pyobfus tools (preflight risk check, zero-config init, reverse stack-trace mapping) directly from an agent conversation.
8
6
Apache 2.0
Why this server?
Utilizes Pydantic for type-safe data models, parameter validation, and structured data handling when generating Excel templates.
A Model Context Protocol (MCP) server that generates Excel templates conforming to JXLS specifications, supporting both JSON objects and arrays data formats.
1
MIT
Why this server?
Enforces execution policies in PydanticAI agents via decorators.
Local zero-trust permission gateway for AI agents. Enforces policy-based tool authorization, human approvals, scoped permissions, and cryptographically verifiable audit logs.
4
5
Apache 2.0
Why this server?
Uses Pydantic models for type-safe data validation and serialization of tool inputs, outputs, and server configurations
A lightweight server implementation that exposes Python functions as discoverable tools via HTTP using the Machine-to-Machine Communication Protocol (MCP). Enables remote execution of Python functions through a JSON-RPC interface with async support and type safety.
4
MIT
Why this server?
Adds governance capabilities to Pydantic AI agents, allowing for policy-based tool execution and human approval workflows.
Governance proxy for MCP servers. Wraps any MCP server with policy evaluation, human approval workflows, and hash-chain audit trails. Supports stdio and Streamable HTTP transports.
