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"Multi-agent AI systems for collaborative code development" matching MCP servers:

  • agent-lsp

    blackwell-systems
    A
    license
    A
    quality
    A
    maintenance
    MCP server that keeps language server sessions warm and routes multiple languages through one process. Agents get persistent cross-file awareness, speculative execution (simulate edits before writing to disk), and 20 skills that encode correct multi-step operations like safe rename, blast-radius analysis, and end-to-end refactoring. Single Go binary, no runtime dependencies.
    50
    107
    MIT

  • agent-tool

    knewstimek
    A
    license
    A
    quality
    A
    maintenance
    Encoding-aware, indentation-smart file tools for AI coding agents. 20+ tools including read/edit with automatic encoding detection, smart indentation conversion, SSH, SFTP, process management, and system utilities.
    53
    24
    MIT

  • agent-guard-mcp

    Kavachh
    A
    license
    -
    quality
    B
    maintenance
    Provides git-aware safe file operations, allowing AI agents to delete files while protecting git-tracked source code from accidental deletion.
    MIT

  • M.I.M.I.R - Multi-agent

    orneryd
    A
    license
    -
    quality
    C
    maintenance
    Provides AI assistants with persistent graph database memory using Neo4j, enabling task management, relationship understanding, semantic search with embeddings, file indexing, and multi-agent coordination through the Model Context Protocol.
    6
    280
    MIT

  • code-graph-mcp

    attaxr
    A
    license
    -
    quality
    B
    maintenance
    Turns a codebase into a queryable graph with semantic search, call graphs, and control/data flow analysis, served to AI coding agents via the Model Context Protocol.
    206
    MIT

  • code-rag-golang

    nullptr-z
    F
    license
    -
    quality
    C
    maintenance
    AI modifies a function but misses 5 callers that also need updating. crag fixes this — it builds precise call graphs via static analysis, so AI knows exactly what's affected before making changes.
    2
  • NetDefense for OPNsense by netdefense-io

    NetDefense for OPNsenseofficial

    netdefense-io
    A
    license
    -
    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

  • Grimoire for Gamemasters

    zafety-vibin
    A
    license
    -
    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

  • Multi Database MCP Server

    FreePeak
    A
    license
    -
    quality
    B
    maintenance
    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.
    411
    MIT

  • agent-memory-mcp

    ipiton
    A
    license
    -
    quality
    A
    maintenance
    A memory, docs, and repo context layer for engineering agents, providing typed persistent memory, RAG document retrieval, and repository-aware tools to recall decisions, runbooks, and operational knowledge across sessions.
    39
    MIT
  • knowing by blackwell-systems

    knowingofficial

    blackwell-systems
    A
    license
    -
    quality
    A
    maintenance
    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
    17
    MIT