Skip to main content
Glama
102,088 servers. Updated

Matching MCP tools:

Matching MCP Connectors:

"A tool for task summarization and team planning" matching MCP servers:

GET /v1/servers – MCP directory API reference
  • A
    license
    B
    quality
    C
    maintenance
    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.
    3
    MIT
  • A
    license
    A
    quality
    D
    maintenance
    A cross-AI-agent local task context sharing MCP server that allows clients like Codex, Claude Code, Hermes, and VS Code to read and write the same task state, enabling task tracking and context distillation.
    6
    MIT
  • A
    license
    A
    quality
    C
    maintenance
    Enables MCP clients like Claude to query Chinese A-share market data, including K-line charts with forward/backward adjustment, limit-up and limit-down pools, per-stock fund flows, index quotes, and stock news, with automatic symbol normalization and retry handling for throttled data sources.
    6
    MIT
  • A
    license
    B
    quality
    C
    maintenance
    Provides A-share (Chinese stock market) quantitative analysis through tools for stock screening, northbound capital flow tracking, dragon-tiger list analysis, margin trading, sector analysis, technical indicators, IPO info, and limit-up/down statistics using akshare data.
    11
    2
    MIT
  • F
    license
    B
    quality
    C
    maintenance
    Enables LLMs to read and write local user data, generate fake users via sampling, and interact with structured prompts and resources.
    2
    -
  • A
    license
    B
    quality
    D
    maintenance
    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.
    9
    MIT
  • A
    license
    A
    quality
    B
    maintenance
    An MCP server that provides utility tools for text analysis, URL metadata fetching, and temperature conversion.
    3
    MIT
  • F
    license
    A
    quality
    D
    maintenance
    Enables document conversion between PDF, DOCX, and Markdown formats to facilitate reading and editing complex files in AI tools like Claude Desktop or Cursor. It utilizes marker-pdf and pandoc to provide structured text versions of documents, helping to manage context and support unsupported file types.
    1
    1
    -
  • A
    license
    A
    quality
    A
    maintenance
    An MCP server that enables AI agents to pause and request human approval or information via Slack, Telegram, or macOS dialogs before proceeding with actions.
    2
    15
    Apache 2.0
  • A
    license
    A
    quality
    C
    maintenance
    Enables AI agents to autonomously manage and improve execution processes for repetitive task types by storing reusable task contexts with associated artifacts (practices, rules, prompts, learnings) and providing full-text search across historical best practices.
    8
    1
    MIT
  • A
    license
    A
    quality
    C
    maintenance
    Read-only MySQL MCP server that lets AI agents list tables, describe schemas, and run SELECT/SHOW/EXPLAIN queries with a row cap, bound to a single database for safety.
    3
    MIT
  • A
    license
    A
    quality
    B
    maintenance
    Graph-based tool retrieval for LLM agents. Builds a tool graph from OpenAPI/MCP specs and retrieves multi-step workflows via hybrid search (BM25 + graph traversal + embedding), recovering accuracy from 12% to 82% with 79% fewer tokens. Also works as an MCP Proxy to aggregate multiple servers behind 3 meta-tools.
    6
    273 PyPI
    17
    MIT
  • A
    license
    A
    quality
    A
    maintenance
    Enables Claude to independently check an AI agent's work in a local git repository by recording a baseline, running only the checks relevant to the changed files, and cross-checking what the agent claimed. Returns a compact, evidence-labelled report with a verdict and a ready-to-paste next prompt, so unverified success claims can't slip through.
    8
    MIT