"Project dependency resolution and analysis" matching MCP servers:

An MCP server that performs comprehensive health checks on project dependencies for JavaScript and Python projects, detecting outdated packages and fetching changelogs.

Enables local analysis of unstructured documents (PDF, DOCX, PPTX, SVG, PNG) by extracting text and structure with citation anchors, and verifies summaries against source material before a human approves saving a report.

AI-powered terrain analysis for any location on Earth. Uses super-resolution and computes environmental risk metrics including erosion, water flow, and a composite Site Intelligence Score.

FastMCP server for image analysis providing OCR, metadata, and EXIF extraction.

Records and scores prospective equity earnings predictions made by AI agents, allowing comparison of different agent configurations.

Intent-based project documentation server that automatically maps natural language queries to the right sources (plans, todos, roadmap, docs) and provides comprehensive task management with dependency tracking, backlog promotion, and archival workflows.

Self-hostable, read-only Taiwan stock-analysis MCP server that retrieves market data and computes reproducible indicators.

A FastMCP server that exposes predefined artifacts as Resources and project lifecycle operations as Tools for creating, updating, deploying, debugging, testing, monitoring, and configuring projects with minimal token usage.

Enables querying options chains and estimating gamma exposure for ETFs and liquid underlyings, including proxy gamma calculations and historical gamma snapshots.

Enables auditing emails for internal contradictions and reporting detected incoherences with literal textual evidence, without issuing a phishing verdict.

Analyzes Python project structure by exploring directory trees, extracting outlines from Python and Markdown files, and inspecting OpenAPI specifications.

Relays a result screenshot to Slack so you can review a coding agent's output without opening the app.

Sentiment Analysis AI - MCP server providing AI-powered tools and automation by MEOK AI Labs

A local-first Model Context Protocol server that provides LLM agents with structured access to e-commerce data (products, inventory, orders, sales analytics) using a realistic mock dataset, zero configuration, and a swappable DataProvider interface for live APIs.

Enables building and evaluating LangGraph agents over a protocol-level MCP server to measure failure rates across four agent topologies.

A read-only MCP server for exploring and analyzing a Secoda data catalog, enabling AI chat, semantic search, glossary browsing, and data lineage tracing.

MCP server that parses aviation accident reports (PDF/DOCX/TXT) and injects their content into extraction prompt templates for knowledge graph construction.

A Python framework that exposes developer tools through MCP, REST API, and CLI from a single shared registry, enabling AI assistants, HTTP clients, and terminal users to access the same tools.

A stateful MCP server that remembers what your AI agent has already seen.

Read-only MCP server that lets analysts pull Yahoo Finance data and compute risk metrics, technical indicators, fundamental and peer ratios, ETF tracking statistics, plus user-defined parametric indicators, conditions and saved hooks with chart output. Every result carries its unit, formula source, data window and warnings, so the agent can explain each number.