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    rhizome-mcp is a local-first MCP server for task tracking and coordination of autonomous AI coding agents, providing crash-safe issue claiming, durable project memory, and dependency graphs using SQLite. It enables agents from different MCP-compatible clients to share a consistent view of project work with no accounts, Docker, or network dependency.
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    Apache 2.0
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    Your coding agent can read the code. It can't read the argument behind it. lema-mcp gives your agent the recorded why — and the alternatives a project already ruled out — cited to the source. For React, Kubernetes, and Rust out of the box, and for your own repo with one command.
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    MIT
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    This project implements a simple MCP server in Go that exposes a single tool (create_short_link) to generate short URLs using the Rebrandly API.
    MIT
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    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.
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    MIT
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    Neo4j MCP Canary is a fast-moving, experimental release of the Neo4j MCP server for customers who want to explore emerging capabilities before they are considered for the official server.
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    ZCP is a CLI with Zerops MCP that makes your agent a Zerops power-user. It runs either inside your project, or is connected through zCLI's VPN functionality to the project from your terminal. Your agent. Your subscription. Your code. Your infrastructure. Your IDE.
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    The Multi DB MCP Server is a high-performance implementation of the Database Model Context Protocol designed to revolutionize how AI agents interact with databases. Currently supporting MySQL and PostgreSQL databases.
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    MIT
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    Provides long-term local memory for AI coding agents via MCP, enabling persistent recall of preferences and project facts across chat sessions.
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    MIT
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    Once configured, you can use natural language commands like: "Search for failed builds in the last week" "Why last deploy was failed" "Search the most failed builds" "Trigger a build for the main branch" "Show me recent builds for project X" "Pin the latest successful build" "Cancel the running bui
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    MIT
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    An MCP front-end for AnB. The tool surface is "use-don't-reveal": no tool returns a plaintext secret. Reveal paths require a TTY the server doesn't have, so the no-reveal guarantee is structural, not prompt-based — it holds even against a prompt-injected agent. Runs as a dedicated, narrowly-scoped AnB identity; exec is default-deny (only allowlist rules tagged scope=mcp run); command output
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    MIT
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    Local-first MCP server providing semantic search over library docs, fully offline. Single Go binary speaks MCP over stdio against a vector index pinned to the binary version. Like Context7 with the internet turned off. Apache 2.0. Linux + macOS, also available as a container image.
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    An MCP server that gives AI agents structured read/write access to a story-based project backlog. Agents can list stories, read content, update status, and append notes — all backed by plain markdown files that live inside your project repository. There is no shared server. The backlog files live in your repo under requirements/, committed and versioned alongside your code
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    The Unlicense
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    A deterministic symbol oracle over a locally built index of the repository: whether a symbol exists, what a file declares, and what changed structurally since the last snapshot. It also ships a PreToolUse guard that stops an Edit/Write referencing a function, constant or type the repo does not declare, before the write lands rather than after the build fails. No LLM, no API keys, no network, no l
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    MIT
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    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.
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    Apache 2.0
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    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.
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    Apache 2.0
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    Failure Memory provides AI coding agents with a shared local memory of failures, enabling them to record, recall, and learn from mistakes across sessions.
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    MIT
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    A WorkFlowy MCP Server with node creation, recursive gets, updates, completions, search and replace (with a dry run mode), usage reports, a configurable list of exposed commands and customizable log output.
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    MIT