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    An offline-first MCP server for querying Google ADK documentation using vector search, enabling AI models to access and understand ADK docs.
    1
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    A minimal MCP server with get_weather and create_ticket tools, used for testing MCP servers across protocol, unit, eval, transport, and auth layers.
    MIT
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    Enables MCP clients to extract validated typed records from unstructured text using named schemas, with schema listing and extraction tools. It returns validated JSON or tool errors, optionally using an offline parser or an OpenAI-compatible model with retries on validation failures.
    2
    MIT
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    Enables an LLM to maintain and query durable layered context across sessions, retrieving standing rules, current state, open loops, compiled pages, historical facts, and hard records with explicit conflict handling and abstention when nothing matches.
    20
    MIT
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    Enables AI agents to run brand-visibility audits by querying multiple AI engines, generating competitive leaderboards, and identifying growth opportunities. Integrates with any MCP-capable client to measure and act on brand discoverability in AI recommendations.
    MIT
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    Enables unified access to SAP S/4HANA material management and Salesforce CRM customer telemetry through Google ADK, with schema reflection for dynamic integration.
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    MCP server providing governed access to board meeting data, with tools to query meetings, motions, and documents, automatically applying anonymity policies before returning answers.
    6
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    Ultra-fast local markdown documentation RAG for AI coding agents, enabling instant BM25 search over official framework docs and live AI model registries via MCP.
    8
    22 PyPI
    2
    MIT
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    Enables AI coding agents to synthesize and play concise spoken summaries of their work through multiple TTS providers, including Azure, OpenRouter, OpenAI, Gemini, ElevenLabs, and local OpenAI-compatible endpoints. It also lets agents stop playback on demand and check which provider, voice, and audio bridge are currently active.
    4
    33 PyPI
    1
    MIT
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    An MCP server that exposes ISO 20022 postal-address classification, assessment, and remediation tools for AI agents, enabling them to prepare debtor/creditor addresses for the November 2026 structured-address cutover.
    13
    33 PyPI
    1
    Apache 2.0
  • A
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    Enables an AI agent to launch, monitor, and steer multiple coding agents running in tmux panes, including sending keystrokes, waiting for idle or output patterns, and managing sessions.
    9
    32 PyPI
    1
    MIT
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    Local MCP server for specialist personas, reusable Markdown workflows, task-scoped subagent contracts and per-repository memory. Runs on your own computer with Python 3.11+ and a locally installed embedding model; its Claude Code plugin launches that separate installation.
    2
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    14
    MIT
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    GOSCE Portfolio Router Single entry point for the GOSCE agent portfolio. Routes orchestrators to verified agents by capability with real example outputs from live self-test probes. Quality-assured broker, not a static directory. Structured Output MCP Agent Turn a prompt and field schema into validated, typed JSON using Instructor over Gemini 2.5 Flash. Ideal for extracting structured entities from
    9
    1
    MIT
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    A local markdown memory and cross-agent context engine for AI coding assistants. It provides an MCP server with tools to search, add, retrieve, and distill persistent memory across tools like Claude Code, Cursor, and Zed.
    37 PyPI
    5
    MIT