"How to organize or locate my project file" 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.

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

A secure MCP proxy server with JWT authentication, SQL guardrails, rate limiting, and Kafka audit logging, enabling enterprise-grade access control for MCP clients like Cursor and Claude Desktop.

Enables secure analysis of log files by listing, summarizing, and searching for error patterns, with defenses against path traversal, symlink attacks, and data leakage.

Privacy friendly, cookieless web analytics built MCP-first. "Add analytics to my Next.js app" → an AI agent runs the setup_analytics_for_site tool, picks the right install snippet, edits your layout file, and verifies the script is loading. OAuth onboarding, no API keys to paste.

An MCP server that enables coding agents to log their work, decisions, test runs, PRs, and progress as structured events, either to a local JSONL file or an HTTP endpoint.

Enables AI assistants to query, search, and analyze logs across Google Cloud Platform projects. It supports advanced filtering by severity or resource type and provides detailed log entry retrieval and project listing capabilities.

Enables remote log searching, tailing, and file reading across servers via MCP tools, with pluggable execution via SSH, pyinfra, or local commands.

Analyzes how search engines and AI systems discover, crawl, cite, and convert traffic via CLI and MCP tools.

An MCP filesystem telemetry server that watches directories and records every file change with SHA-256 hashes, enabling verification of edits through tools like recent_changes and query_events, with multi-project support and idle suspension.

Local MCP server that lets your AI coding agent query its own cross-tool project history - file/command freshness, past test failures, cost & token spend, cache status, and session handoff - over stdio, 100% local, no telemetry.

A local-first MCP server that gives AI coding agents runtime visibility and AI-managed debug logging. It replaces blind print() debugging by turning runtime execution into causal chains, allowing agents to instantly locate bugs by finding missing .success events in Python and TypeScript code. Single binary with MCP, CLI, and HTTP interfaces.

Enables AI agents to monitor server health and capacity, diagnose outages, inspect Docker and deployment status, and perform safe, bounded recovery actions via MCP without granting unrestricted shell or SSH access.

An MCP server that exposes a dbt project's run state as tools, enabling AI assistants to answer questions like 'is the warehouse healthy?' or 'what broke and why?' via plain English, using read-only access to dbt artifacts and warehouse data.

Enables coding agents to read performance findings from sixty, get detailed evidence for each finding, and close or resolve them with descriptions, while also checking service telemetry and providing installation instructions.

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 analyzing Perfetto traces with LLMs — query .pftrace files in PerfettoSQL via Claude Code or any MCP client

Enables AI agents to check the health of internet infrastructure and specific services, helping diagnose whether issues are local or external.

This MCP server enables AI assistants to read PBX state—extensions, DID numbers, SIP trunk providers, tenants, and live statistics—from ICTPBX via the ICTCore REST API, without placing calls or changing configuration.