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© 2026 TrackMCP. All rights reserved.

Built with ❤️ by Krishna Goyal

    Filescopemcp

    Analyzes your codebase identifying important files based on dependency relationships. Generates diagrams and importance scores per file, helping AI assistant...

    252 stars
    HTML
    Updated Nov 4, 2025

    Table of Contents

    • Key Features
    • Prerequisites
    • Quick Start
    • Agent Runtimes (Hermes, Codex, OpenClaw)
    • LLM Summaries (Optional)
    • LLM Monitoring (Optional)
    • MCP Tools
    • Nexus Dashboard
    • How It Works
    • Documentation
    • License

    Table of Contents

    • Key Features
    • Prerequisites
    • Quick Start
    • Agent Runtimes (Hermes, Codex, OpenClaw)
    • LLM Summaries (Optional)
    • LLM Monitoring (Optional)
    • MCP Tools
    • Nexus Dashboard
    • How It Works
    • Documentation
    • License

    Documentation

    FileScopeMCP

    Your AI already knows how to code. Now it knows your codebase.

    Build Status

    Node.js

    License

    Trust Score

    FileScopeMCP watches your code, ranks every file by importance, maps all dependencies, and keeps AI-generated summaries fresh in the background. When your LLM asks "what does this file do?" — it gets a real answer without reading the source.

    Works with Claude Code, Hermes Agent, Codex, OpenClaw, Cursor AI, or as a standalone daemon. Supports TypeScript, JavaScript, Python, C, C++, Rust, Go, Ruby, Lua, Zig, PHP, C#, and Java.

    Key Features

    Importance ranking — every file scored 0-10 based on how many things depend on it, what it exports, and where it lives. Your LLM sees the critical files first.

    Dependency mapping — bidirectional import tracking across all supported languages. AST-level extraction (tree-sitter) for TS/JS, Python, C, C++, Rust, Go, and Ruby; regex-based for Lua, Zig, PHP, C#, and Java. Finds circular dependencies too.

    Symbol intelligence — extracts functions, classes, interfaces, types, enums, consts, modules, and structs from source via tree-sitter. find_symbol resolves names to file + line range. find_callers and find_callees map the call graph for TS/JS so your AI can answer "who calls this function?" before refactoring.

    Always fresh — file watcher + semantic change detection means metadata updates automatically. AST-level diffing for TS/JS, LLM-powered analysis for everything else. Only re-processes what actually changed.

    LLM broker — a background process coordinates all AI work through llama.cpp's llama-server (or any OpenAI-compatible HTTP API). Priority queue ensures interactive queries beat background processing. Runs on a single GPU.

    Nexus dashboard — a web UI at localhost:1234 that lets you visually explore your codebase across all your repos. Interactive dependency graphs, file detail panels, live broker activity, and per-repo health monitoring.

    Prerequisites

    • Node.js >= 22 and npm (download)
    • Build tools for native modules (better-sqlite3, tree-sitter):
    • Linux: sudo apt install build-essential python3
    • macOS: xcode-select --install
    • Windows: Visual Studio Build Tools with C++ workload

    Quick Start

    bash
    git clone https://github.com/admica/FileScopeMCP.git
    cd FileScopeMCP
    ./build.sh          # installs deps, compiles, registers with Claude Code

    ./build.sh registers FileScopeMCP globally via claude mcp add --scope user (idempotent; re-run with npm run register-mcp). If the claude CLI is missing, the build still succeeds — see docs/mcp-clients.md for other MCP clients.

    Open a Claude Code session in any project and FileScopeMCP auto-initializes. The MCP tools appear automatically — your AI can call them directly during conversation:

    code
    find_important_files(limit: 5)
    status()

    Agent Runtimes (Hermes, Codex, OpenClaw)

    Agent runtimes discover FileScopeMCP via the repo's AGENTS.md, which includes MCP registration config, broker/LLM setup, and a pointer to the portable skill file at skills/filescope-mcp/SKILL.md.

    Hermes — add to ~/.hermes/config.yaml:

    yaml
    mcp_servers:
      filescope:
        command: "node"
        args: ["/path/to/FileScopeMCP/dist/mcp-server.js"]
        timeout: 120

    Already have a local LLM running? Point the broker at it — edit ~/.filescope/broker.json and set baseURL to your LLM's endpoint. See AGENTS.md for details.

    LLM Summaries (Optional)

    Run ./setup-llm.sh for a platform-specific guide to setting up llama.cpp's llama-server — see docs/llm-setup.md for details. On Linux you can also sudo ./setup-llm.sh --install-service to register llama-server as a systemd unit (logs flow to journalctl, OOM-protected, auto-restart on boot). The flag is a no-op under WSL2 since llama-server runs on the Windows host there. Without llama-server entirely, everything else still works (file tracking, dependencies, symbols, call graphs — just no LLM-generated summaries). If your agent runtime already has a local LLM, configure the broker to reuse it instead.

    Add to your project's .gitignore:

    code
    .filescope/
    .filescope-daemon.log

    LLM Monitoring (Optional)

    If llama-server is running locally, an optional VictoriaMetrics + vmui stack gives you a single-pane dashboard for VRAM, RAM, swap, throughput, and cumulative work. Total resident footprint ~120 MB, capped via systemd cgroups so a misbehaving exporter can't OOM-kill llama-server.

    bash
    sudo ./monitoring/install.sh

    Browse the dashboard at http://:8881/vmui/#/dashboards. See monitoring/ for the layout and uninstall script.

    MCP Tools

    ToolWhat it does
    statusBroker connection, queue depth, LLM progress, watcher state
    find_important_filesTop files by importance score with dependency counts
    get_file_summaryEverything about a file: summary, concepts, change impact, exports, deps, staleness
    list_filesFull file tree (no args) or flat top-N by importance (with maxItems)
    find_symbolResolve a symbol name to file + line range; supports prefix match via trailing *
    find_callersFind all symbols that call a named symbol (TS/JS call graph)
    find_calleesFind all symbols that a named symbol calls (TS/JS call graph)
    searchSearch file metadata across symbols, summaries, purpose, and paths
    list_changed_sinceFiles changed since a timestamp or git SHA
    get_communitiesLouvain-clustered file groups by import coupling
    detect_cyclesFind circular dependency chains
    get_cycles_for_fileCycles involving a specific file
    scan_allQueue files for LLM summarization via the broker
    set_base_directoryPoint at a different project
    set_file_summaryManually set or override a file's LLM summary
    set_file_importanceManually set a file's importance score (0-10)
    exclude_and_removeDrop files/patterns from tracking (destructive)

    Nexus Dashboard

    bash
    npm run build:nexus  # one-time build (API + UI)
    npm run nexus        # starts at http://localhost:1234

    A read-only web dashboard that connects to every FileScopeMCP repo on your machine:

    • Project view — file tree with importance heat colors and staleness indicators, click any file for full metadata
    • Dependency graph — interactive Cytoscape.js visualization, filter by directory, click nodes to inspect
    • System view — live broker status, per-repo token usage, streaming activity log
    • Settings — manage which repos appear, remove or restore from blacklist

    Auto-discovers repos by scanning for .filescope/data.db directories. No configuration needed.

    How It Works

    code
    Your code changes
        → file watcher picks it up
        → AST diff classifies the change (exports? types? body only?)
        → symbols extracted (functions, classes, types, etc.)
        → call-site edges resolved (TS/JS: who calls what)
        → importance scores recalculated
        → staleness cascades to dependents (only if exports/types changed)
        → LLM broker regenerates summaries, concepts, change impact
        → your AI's next query gets fresh answers

    Everything lives in .filescope/data.db (SQLite, WAL mode) per project. The broker coordinates LLM work across all your repos via a Unix socket at ~/.filescope/broker.sock.

    Documentation

    DocWhat's in it
    AGENTS.mdCross-agent context file — MCP registration, broker config, architecture (read by Hermes, Codex, OpenClaw)
    FileScopeMCP SkillPortable skill file — tool reference, workflows, tips for agents using FileScopeMCP
    LLM Setupllama.cpp / llama-server installation — Linux/macOS native (default), WSL2+Windows, or remote LAN
    ConfigurationPer-project config, broker config, ignore patterns
    MCP ClientsSetup for Claude Code, Cursor AI, daemon mode
    TroubleshootingCommon issues and fixes
    InternalsDependency detection, importance formula, symbol extraction, call-site edges, storage
    LLM MonitoringOptional VictoriaMetrics + vmui dashboard for the local llama-server

    License

    Copyright (c) 2026 admica. All rights reserved. See LICENSE.

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