"Tor Project" matching MCP servers:

Brings live project context into Slack via MCP, enabling developer teams to check service health, recall team decisions, search code, and query project context directly from chat.

Provides unified project context and monitoring capabilities including project health metrics, build diagnostics, Git integration, and infrastructure validation to initialize development sessions with comprehensive project information.

Connects AI coding assistants to Gaffer test history and coverage data to analyze project health, debug failures, and identify untested code areas. It enables tools to track test stability, cluster failures by root cause, and monitor code coverage trends across projects.

Real-time cost observability for Model Context Protocol tool calls. Wraps any MCP server, attributesspend per tool/project/customer. Free 25K calls/month. EU-hosted, GDPR-ready, MIT.

Enables AI agents to read and optionally write to PostgreSQL databases through a multi-project setup with schema inspection, query execution, and performance analysis tools.

Connects to MES systems for SOP file upload and abnormal report querying via WorkBuddy.

Enables running, monitoring, and managing ANUGA flood simulations on Hydrata Cloud, supporting project listing, scenario queries, simulation start, status polling, cancellation, and retry operations.

Read-only Model Context Protocol server that enables querying Langfuse v4 events-only deployments for traces rebuilt as trees, sessions, searchable observations, scores, server-side metrics aggregates and managed prompts. Supports many projects from one server, taking a project argument per data tool and verifying each key against the project it is filed under before any data is read.

AI development observability platform. It silently captures structured data from vibe coding sessions via MCP and codifies deviation patterns into project rules to make AI write better code. 100% local and zero runtime dependencies.

Connect AI assistants to Sentry for error tracking, issues, releases, events, and project management through the Model Context Protocol. Provides tools to list organizations, projects, issues, events, releases, teams, and members, as well as get details and update issue status.

Enables querying PostHog with HogQL, retrieving event and property definitions, session replays, and project lists, plus optional REST API access with safeguards against accidental writes and API key leakage.

Lets an AI agent read a Pyxis dashboard's analytics — overviews, funnels, devices, acquisition, backend requests, visits and project settings — using a read-only access token created by an admin and revocable at any time. It runs locally over stdio, holds no state, and exposes only GET-style reads of the live Pyxis API.

Auto-discovers MCP servers for your project and tracks ROI per session. One install: npx -y @perceptdot/core. Your agent finds its own tools and reports tokens saved.

Enables LLMs to interact with Kibana through composable toolboxes for building dashboards, managing data, and handling alerts, among other operations.

MCP server for integrating self-hosted Sentry with AI assistants, enabling project and issue listing, issue details with stack traces, and event retrieval.

An unofficial MCP server that connects AI assistants to Akamai APIs, providing tools for edge diagnostics, debugging, and network analysis.

Enables AI clients and IDEs to connect to Firebird 2.5–5.0 databases, managing multiple connections per project through automatic workspace configuration and runtime switching. Provides schema and RDB$ metadata introspection, execution PLAN analysis with indexing suggestions, health auditing, and safely guarded read-only queries alongside controlled DML/DDL execution.

MCP server implementation that enables LLMs to interact with Rollbar error tracking data, allowing users to list and analyze errors, view occurrences, track deployments, and access project information.

Exposes UniFi Protect's Integration REST API as tools for Claude Code and other MCP clients, providing 73 tools to manage cameras, lights, sensors, and more with safety features like read-only mode and dry-run support.

A Model Context Protocol server that enables AI assistants to interact with Sentry for error tracking and monitoring, allowing retrieval and analysis of error data, project management, and performance monitoring through the Sentry API.