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    Enables governed multi-agent software factory operations through eight typed, audited tools for Sprint planning, submission, decisions, inspection, cancellation, and resumption.
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    Provides git-aware safe file operations, allowing AI agents to delete files while protecting git-tracked source code from accidental deletion.
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    MIT
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    Self-hostable, markdown-native team wiki with a built-in MCP server: agents search, read, and write your wiki pages (ranked Postgres full-text + semantic search, backlink traversal). Plus Atlas, which auto-generates a cited, coverage-checked wiki from your git repos and Jira.
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    AGPL 3.0
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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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    A high-performance MCP server providing up-to-date documentation for Go, npm, Python, Rust, Docker, Kubernetes, Terraform, and more — fetched from official sources, not training data.
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    MIT
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    MCP server that reads Duplicacy backup metrics from a Prometheus exporter and exposes them to LLMs for monitoring backup status, progress, and health.
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    GPL 3.0
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    Content-addressed code graph that produces ranked context for AI agents in one call. 22 MCP tools across indexing, blast radius, test scope, semantic diff, runtime traffic, and feedback-aware context packing. Incremental updates via Merkle DAG (no re-indexing). GCF wire format saves 84% tokens vs JSON
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    MIT
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    A Model Context Protocol (MCP) server for Grafana. This provides access to your Grafana instance and the surrounding ecosystem.
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    3,279
    Apache 2.0
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    Enables AI assistants to query databases using natural language, with automatic schema discovery and SQL compilation.
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    3,130
    Apache 2.0
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    Enables SQL queries against PostgreSQL databases through MCP-compatible clients and includes a natural language agent for forming SQL queries from natural language.
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    203
    PostgreSQL
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    A Model Context Protocol server implementation for Axiom that enables AI agents to query your data using Axiom Processing Language (APL).
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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.
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    MIT
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    ToolMesh is an Apache-2.0, self-hosted MCP gateway written in Go that sits between AI agents and backend systems. It enforces a fail-closed pipeline on every tool call, including per-tool and per-user authorization, server-side credential injection, structured audit logging, and output policies. APIs are declared in YAML with DADL, turning REST endpoints into MCP tools without writing a custom MCP
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    Apache 2.0
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    Enables AI coding assistants to search and retrieve information from a locally ingested knowledge base using hybrid search, grounded in user-curated documentation.
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    MIT