"Tor Project" matching MCP servers:

A comprehensive project management and workflow tracking system that integrates with Claude Code via MCP, automatically capturing sessions, tools, agents, and project tasks into a centralized dashboard and database.

MCP server that provides read-only analysis of Claude Code session transcripts, enabling queries about project activity, session details, and tool usage.

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.

MCP server for managing a Nitrado-hosted Project Zomboid server. It lets you check status, edit sandbox settings, manage mods, and tail logs through natural language.

Fetches Langfuse observability traces directly into a VS Code coding agent's context, enabling querying and viewing trace data through natural language.

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.

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.

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.

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.

Enables AI-driven SOC investigations by providing automated Splunk querying, threat intelligence enrichment, and response actions through natural language. Includes tools for IP pivoting, lateral movement detection, and label harvesting.

A read-only MCP server that lets AI clients investigate logs stored in VictoriaLogs over stdio, offering LogsQL search, UUID/stream lookups, stream and field discovery, hit aggregation, and stats queries with time-range and filtering controls. It supports bearer, basic, or anonymous auth, multi-tenant account/project IDs, and response size and timeout limits.

Enables AI agents to interact seamlessly with Splunk environments through 20+ tools for search, analytics, data discovery, administration, and health monitoring. Features AI-powered troubleshooting workflows and supports multiple Splunk instances with production-ready security.

A Model Context Protocol server that provides seamless integration with Coroot observability platform, enabling monitoring of applications, analysis of performance metrics, examination of logs and traces, and management of infrastructure through Coroot's comprehensive API.

Enables interaction with Sentry's error tracking platform to fetch and manage issue details, events, and project information through the Sentry API.

An MCP server implementation that integrates AI assistants with Langfuse workspaces, allowing models to query LLM metrics by time range.

Provides a standardized way for MCP clients to interact with Apache Airflow's REST API, supporting operations like DAG management and monitoring Airflow system health.

Enables MCP clients to create and list error-tracking projects and investigate grouped exception issues using captured OTLP error data. It provides admin-token-secured tools for project setup and issue investigation.

A comprehensive, AI-powered performance analysis and monitoring platform for OpenShift/Kubernetes clusters. This project provides Model Context Protocol (MCP) servers for analyzing etcd, network, and OVN-Kubernetes components with deep performance insights, automated root cause analysis, and actionable recommendations.