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  • A
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    quality
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    maintenance
    Provides AI coding assistants with code search, impact analysis, task chaining, and persistent memory to turn AI demos into deliverable code.
    16
    MIT
  • A
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    quality
    A
    maintenance
    Manage a fleet of OPNsense firewalls from an AI agent, inside guardrails it can't drive around. MCP server for central management of OPNsense firewall fleets. 129 tools across devices, config sync, tasks, schedules, templates, backups and remote consoles - destructive actions confirmation-gated, MCP-issued tokens lifetime-bounded, backup and storage secrets excluded from the toolset entirely.
    Apache 2.0
  • A
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    quality
    B
    maintenance
    Connect to your TTRPG campaign's repository and database. Instead of retrieving prose, its 48 tools (20 read, 28 write) return typed state: 14 entity schemas (NPCs, factions, locations, sessions, lore), relationship and knowledge-graph queries, wiki blocks, and a narrative-state bundle of open threads and canon facts.
    1
    MIT
  • A
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    quality
    A
    maintenance
    CNN's Fear & Greed index for the US stock market: current score and rating, the seven component indicators, and about a year of daily history. Go standard library only, no API key required.
    2
    MIT
  • A
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    quality
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    MCP server that enables AI assistants to drive systematic literature review workflows, including screening, downloading, converting, and reviewing papers through natural language conversation.
    27
    AGPL 3.0
  • A
    license
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    quality
    D
    maintenance
    An MCP (Model Context Protocol) server for managing Tailscale resources using the official Tailscale Go client library v2. This server provides complete coverage of the Tailscale API with enhanced, self-descriptive tools powered by OpenAPI documentation.
    2
    MIT
  • F
    license
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    quality
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    maintenance
    Model Context Protocol (MCP) server for the Royal Spanish Academy (RAE) API. It allows language models to interact with RAE's dictionary and linguistic resources.
    6
  • A
    license
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    quality
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    maintenance
    A local AST and type-aware Go repository context indexer that uses CHA to map symbols, call graphs, dependencies, and architecture patterns. Built for AI coding agents that need to navigate and reason about large Go codebases without reading raw files.
    65
    208
    MIT
  • A
    license
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    quality
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    maintenance
    Local-first shared memory and task coordination for AI coding agents. One Go binary, MCP server, markdown files you own. Hooks for Claude Code and Codex CLI (and their desktop apps).
    6
    30
    3
    MIT
  • A
    license
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    quality
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    maintenance
    Coordination for parallel coding agents: TTL file claims stored in the git common dir (visible across all worktrees), enforcement hooks that block colliding edits, agent presence, handoff notes, and a git-committed lessons knowledge base with BM25 search. Single static Go binary — no server, no database.
    8
    MIT
  • A
    license
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    quality
    A
    maintenance
    A high-performance, multi-protocol API mock server with 18 built-in MCP tools for managing HTTP, GraphQL, gRPC, WebSocket, MQTT, SSE, and SOAP mocks, chaos engineering, stateful CRUD resources, and request verification.
    18
    141
    Apache 2.0
  • A
    license
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    quality
    A
    maintenance
    MCP server for gavel, a code-quality gate for Bazel monorepos. Exposes judge, findings, coverage and architecture tools so a coding agent can check its change against the quality gate (lint, coverage, layer rules) before declaring it done — all off the Bazel build graph, over just what changed.
    8
    8
    Apache 2.0
  • A
    license
    A
    quality
    C
    maintenance
    Portable memory protocol for AI coding sessions. Push the state of a session (goal, decisions, attempts, next step) from one MCP-capable agent and pull it back from another.
    12
    8
    Apache 2.0
  • A
    license
    A
    quality
    A
    maintenance
    Failure Memory provides AI coding agents with a shared local memory of failures, enabling them to record, recall, and learn from mistakes across sessions.
    2
    MIT