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  • MCP Agentic Framework

    Piotr1215
    F
    license
    A
    quality
    C
    maintenance
    A communication framework that enables multiple AI agents to collaborate through asynchronous messaging, agent registration, and discovery. It facilitates complex task coordination and real-time discussion across distributed agent workflows using the Model Context Protocol.
    9
    11

  • Multi MCP

    itstanner5216
    A
    license
    B
    quality
    D
    maintenance
    A flexible proxy server that aggregates multiple backend MCP servers into a single interface using STDIO or SSE transports. It supports dynamic server management via an HTTP API and utilizes namespacing to prevent tool conflicts across connected services.
    3
    1
    MIT

  • sap-abap-mcp

    Coaspe
    A
    license
    C
    quality
    A
    maintenance
    A local MCP server that connects to SAP ABAP systems via ADT HTTP API, enabling AI assistants to search, read, and manage ABAP objects securely without SAP GUI.
    120
    491
    3
    MIT

  • japan-seasons-mcp

    haomingkoo
    A
    license
    A
    quality
    A
    maintenance
    Live Japan seasonal travel data from Japan Meteorological Corporation. 12 tools covering cherry blossom (sakura) forecasts, autumn leaves (koyo), fruit picking, flowers, festivals, and 3-day weather. 1,700+ GPS-tagged spots updated daily at 9AM JST. Works via npx or hosted HTTP endpoint — no auth required.
    17
    153
    1
    MIT

  • PTY MCP Server

    almahdi
    A
    license
    A
    quality
    D
    maintenance
    A TypeScript-based server that enables programmatic management of pseudo-terminal sessions. It allows users to spawn, control, and interact with terminal processes in real-time through the Model Context Protocol.
    5
    19
    AGPL 3.0

  • Gitlab MCP Server

    jmrplens
    A
    license
    A
    quality
    A
    maintenance
    Model Context Protocol (MCP) server for GitLab — exposes 1006 GitLab REST & GraphQL API operations as MCP tools (42 meta-tools / 57 enterprise), 24 resources, 38 prompts, and 17 completion types for AI assistants. Written in Go, single static binary, stdio and HTTP transport.
    2
    31
    MIT

  • Nanostores MCP

    Valyay
    A
    license
    A
    quality
    D
    maintenance
    The MCP server for Nanostores that scans your codebase with AST analysis to find stores, subscribers, and dependency chains, and can ingest live events to spot noisy, error-prone, or unused stores.
    12
    69
    1
    MIT

  • mcp-whatsapp

    Sealjay
    A
    license
    A
    quality
    B
    maintenance
    Single-binary Go MCP server that wraps whatsmeow to expose a personal WhatsApp account as 41 MCP tools (messaging, groups, polls, media, privacy).
    42
    7
    MIT

  • mistral-mcp

    Swih
    A
    license
    A
    quality
    C
    maintenance
    mistral-mcp is a TypeScript MCP server (spec 2025-11-25) that exposes the full Mistral AI API surface: 22 tools: chat, OCR, audio (Voxtral), vision, agents, embeddings, moderation, classification, files, batch, sampling, FIM (Codestral), streaming 2 resources: mistral://models, mistral://voices 6 curated prompts (French + English) with MCP argument completion Dual transport: stdio (default) + Str
    8
    292
    16
    MIT

  • idnow-mcp-server

    DevMohith
    F
    license
    A
    quality
    B
    maintenance
    An MCP server that lets LLM agents operate the IDnow Trust Platform sandbox to list verification flows, create sessions, check sessions, and get session details.
    4

  • festo-codesys-mcp

    efranceschetti
    A
    license
    A
    quality
    A
    maintenance
    An MCP server that turns AI assistants into competent Festo/CODESYS PLC engineers by grounding them in curated, manufacturer-accurate knowledge and forcing every artifact through a machine-checked validation pipeline for CODESYS import.
    18
    58
    1
    MIT

  • agentflow-mcp

    ishfuseini
    A
    license
    A
    quality
    B
    maintenance
    Provides enterprise architecture knowledge tools that ground agents in curated patterns, enabling translation of messy enterprise asks into realistic architecture recommendations, platform selection, risk checks, and brand context retrieval.
    4
    2
    MIT