"Asana: Project Management and Team Collaboration Tool" matching MCP servers:

Enables interaction with Asana projects and tasks via the Asana API, supporting listing projects/tasks, creating/updating tasks, and adding comments, with secure authentication and rate-limit handling.

Enables collaboration with multiple AI providers (Claude, GPT-4, Gemini, Ollama) directly from VS Code with automatic project context injection and persistent conversation history. Provides streamlined tools for getting AI advice, multi-provider research, and enhanced context sharing across sessions.

Enables AI agents to interact with collaborative Jupyter notebooks and documents in real-time, supporting notebook operations, document editing, user awareness tracking, and session management through Jupyter's RTC capabilities.

Enables AI agents to join one shared room over MCP where they message each other, post live status, read and write shared notes, and use shared connections such as Zapier, all from a single self-hosted process. Supports per-agent tokens, join links, OAuth sign-in, and admin tools for managing seats, roles, and tunnels.

Provides tools for managing project knowledge graphs, enabling structured representation of projects, tasks, milestones, resources, and team members.

Read, search, and write Obsidian vault notes via Team Relay collaborative server. Supports shared folders, real-time sync, and AI agent access.

Enables orchestrating a reusable team of expert agents (PM, architecture, development, QA, security) to analyze a project's files and produce consolidated recommendations. It exposes tools to list experts, ask a single expert, or run the full team from MCP clients.

Enables users to leverage a team of specialized AI agent personas like Business Analysts and Product Managers through a unified interface across multiple LLM providers. It streamlines agile development workflows by providing tools for model discovery, unified prompt delivery, and role-specific decision making.

Semantic navigator for MCP tools that finds relevant tools by natural language intent, reducing token usage by 95%.

Shared team memory for AI coding agents with Bayesian confidence scoring and temporal decay, enabling persistent storage and retrieval of engineering patterns across sessions.

Enables AI agents to discover and execute tools via a secure MCP server with JWT authentication, RBAC, rate limiting, and audit logging.

Provides AI-driven project memory management through structured prompts that help Claude parse tasks from specs, review code changes, sync with commit history, and maintain project documentation without directly accessing files.

Manage Job using MCP: Manage Job, Candidates, Resumes, Salaries all within this one MCP tools It can solve problems like: You have 50 resumes to screen. Your AI assistant can reason about candidates, but it can't: Read PDFs/DOCX — The AI can't open binary files Extract structured data — Copy-pasting loses formatting, metrics, and context Compare at scale — No consistent scoring across candida

An MCP server implementation of Anthropic's Think Tool prompt engineering technique that enables Claude to break down complex problems and enhance its reasoning capabilities by providing a simple tool that echoes back thoughts.

Enables AI assistants to natively execute and manage 600+ Kali Linux security, penetration testing, and forensic tools, including search, help documentation, structured scanners, and workspace management.

Enables task management (create, list, update tasks with priority and status) using SQLite storage via MCP tools.

An MCP server that transforms text into knowledge graphs and autonomously generates insights by combining Montague Grammar with Zettelkasten methodology.

Enables structured robustness and security testing by scanning text for policy/safety issues and generating test suite outlines.

Enables users to connect to their email inbox via IMAP to search, filter, and summarize emails based on criteria like subject, date, and sender. Supports marking emails as read and provides customizable email summarization with various prompt options.

Enables AI assistants and MCP clients to search Pyaterochka stores, browse categories, find products with filters for price, brand, and promotions, and retrieve product details, store hours, and promotion conditions through the exposed MCP tools.

It enables users to interact with a codebase through hybrid retrieval, code graph navigation, impact analysis, and context preparation for AI coding agents.

A powerful Model Context Protocol (MCP) tool for exploring and managing different types of databases including PostgreSQL, MySQL, and Firestore.

Enables geospatial analysis by chaining MCP tools that resolve areas, select datasets, pull statistics, and generate insights, with session state passing data between tools.

Enables MCP clients to connect to a privacy-first, self-hostable workout planning and training log, allowing coaching agents to preview and apply program changes while accessing training data through OAuth-protected endpoints.

An MCP server that implements the 'think' tool, providing Claude with a dedicated space for structured thinking during complex problem-solving tasks to improve reasoning capabilities.

Enables AI agents to search, filter, and monitor curated AI model API free credits and low-cost token promotions through eight tools, four resources, and three prompts — including finding deals expiring soon, checking eligibility and blocked conditions, and producing daily briefs.

Local MCP server enabling Codex and ChatGPT to read/write files, execute commands, manage processes, use Git, and inspect images on the user's machine with full privileges.

Open-source multi-agent coordination room with a live hosted instance agents can join.

Provides specialized tools for portfolio health analysis, rebalance simulations, and trade execution via a single interface powered by MongoDB. It enables AI agents to manage investment portfolios while adhering to organizational governing rules, clearance guards, and rate limits.

Enables agents to send only the handful of tool definitions relevant to each question, ranking a large catalog by keywords and optional embeddings to cut context cost and wrong-tool picks. It can also run in front of any mcpServers config as a proxy that exposes just search_tools and call_tool instead of the whole catalog.