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ChunkHound MCP Server

Local-first codebase intelligence MCP server that indexes repositories with tree-sitter, stores searchable chunks in DuckDB, and gives Claude semantic search, regex search, daemon status, and deep code research tools.

by ChunkHound · submitted by oktofeesh1·added 2026-06-06·
Review first review before installing

Open the source and read safety notes before installing.

Citation facts

Source-backed facts for citing this resource, derived directly from the registry — also available as plain text for AI assistants.

Source URLs
https://raw.githubusercontent.com/chunkhound/chunkhound/main/site/src/pages/docs/cli-reference.md, https://github.com/chunkhound/chunkhound
Brand
ChunkHound
Brand domain
chunkhound.ai
Brand asset source
brandfetch
Safety notes
ChunkHound reads source files, Markdown, text, PDFs, and supported config files under the target directory and stores indexed chunks in a local database., Realtime indexing and daemon mode can continue watching project files after the initial MCP connection., Code research and web search tools require embedding, reranking, and LLM configuration and may invoke local CLIs or external model APIs depending on settings., Exclude generated files, vendored dependencies, secrets, large artifacts, and unrelated repositories before indexing broad workspace roots., Review MCP client configuration carefully when using an absolute project path in a global Claude Desktop config.
Privacy notes
Indexed chunks, file paths, symbols, comments, Markdown, PDFs, configuration values, database files, daemon state, and search results can reveal proprietary source code and internal architecture., Embedding, reranking, LLM, and web search providers may receive code-derived queries or snippets if configured., Local ChunkHound database files, logs, daemon state, and MCP transcripts may retain code-derived context after the session ends., Avoid sharing ChunkHound databases, config files with API keys, verbose logs, research outputs, and screenshots from private repositories.
Author
ChunkHound
Submitted by
oktofeesh1
Claim status
unclaimed
Last verified
2026-06-06

Decision playbook

Review trust signals before you adopt

Signals are present but mixed. Use the checklist below to confirm the source and operational safety for your environment.

Compare context
Selected

0

Current score

63

Baseline

Delta

No baseline selected

No major trust-signal divergence detected in the current selection.

Source and provenance checks

Needs review

Confirm ownership and provenance before trusting install instructions.

  • Source link availableRequired

    Open the canonical repository and verify ownership.

    Done
  • Source provenance statusRequired

    Marked as source-backed.

    Done
  • Metadata reviewed

    No reviewed flag detected in metadata.

    Pending

Safety and privacy checks

Complete

Validate risk disclosures before installation or API wiring.

  • Safety notes presentRequired

    Review the listed safety guidance before running commands.

    Done
  • Privacy notes presentRequired

    Review data handling notes before connecting accounts or secrets.

    Done
  • Trust level risk gateRequired

    Trust level does not block evaluation.

    Done

Package and install checks

Needs review

Check package metadata and artifact integrity signals.

  • Install payload available

    Install or copy payload is available for review.

    Done
  • Package verification flag

    No package verification flag provided.

    Pending
  • Checksum metadata

    No checksum provided for downloaded artifact.

    Pending

Compare-driven decision checks

Needs review

Use compare context to validate trade-offs before adoption.

  • Compare tray has multiple entries

    Add at least one more entry to compare trust differences.

    Pending
  • Baseline comparison available

    No baseline peer selected yet.

    Pending
  • Diverging trust signals identified

    No major trust-signal divergence found.

    Pending

Setup at a glance

CLI install

Copy-ready — paste the snippet to get started.

15 minutes

Adoption plan

Balanced adoption plan

Current risk score 24/100. Use staged verification before broader rollout.

Risk 24

Pre-adoption checks

Validate source and review signals before any execution.

  • Confirm source provenanceRequired

    Source URL/provenance metadata is present.

    Done
  • Confirm metadata review state

    No review metadata found; increase manual validation.

    Pending
  • Verify install payload

    Install/config payload exists and can be inspected.

    Done

Security checks

Confirm safety, privacy, and package integrity signals.

  • Review safety notesRequired

    Safety notes are present.

    Done
  • Review privacy notesRequired

    Privacy notes are present.

    Done
  • Verify package integrity metadata

    No package verification/checksum metadata.

    Pending

Rollout

Adopt in controlled steps based on the selected plan.

  • Run in isolated sandbox firstRequired

    Use a constrained sandbox and observe behavior across multiple tasks.

    Pending
  • Roll out graduallyRequired

    Roll out to a small cohort before wider usage.

    Pending
  • Set monitoring and fallback

    Define rollback path and monitor errors after adoption.

    Pending

Evidence readiness

Evidence readiness matrix · balanced

Missing required evidence: Metadata review. Risk score 31.

Risk 31

Source provenance

Present

Source repository/provenance is listed.

Required in this preset

Metadata review

Missing

Review metadata is missing.

Required in this preset

Safety notes

Present

Safety notes are present.

Required in this preset

Privacy notes

Present

Privacy notes are present.

Optional in this preset

Package integrity

Missing

Package integrity metadata is missing.

Optional in this preset

Install payload

Present

Install payload is available.

Required in this preset

Required gaps: Metadata review

Decision timeline

Decision timeline · balanced

Blocking gaps: Check metadata review status. Risk 28.

Risk 28

triage

Confirm source provenanceRequired

Source/provenance metadata is available.

Done

triage

Check metadata review statusRequired

Review metadata is missing.

Pending

verify

Review safety notesRequired

Safety notes are available.

Done

verify

Review privacy notes

Privacy notes are available.

Done

verify

Validate package integrity metadata

Package integrity metadata is missing.

Pending

rollout

Verify install payload and commandsRequired

Install payload is available.

Done

Blockers: Check metadata review status

Prerequisite readiness

Prerequisite readiness

5 prerequisites to line up before setup. Have accounts and credentials ready first. Includes a review or approval gate.

0/5 ready
Account & credentials2Install & runtime1Review & approval215 minutes

Safety & privacy surface

Safety & privacy surface

5 safety and 4 privacy notes across 4 risk areas. Review closely: credentials & tokens, third-party handling.

4 areas
  • SafetyLocal filesChunkHound reads source files, Markdown, text, PDFs, and supported config files under the target directory and stores indexed chunks in a local database.
  • SafetyLocal filesRealtime indexing and daemon mode can continue watching project files after the initial MCP connection.
  • SafetyGeneralCode research and web search tools require embedding, reranking, and LLM configuration and may invoke local CLIs or external model APIs depending on settings.
  • SafetyCredentials & tokensExclude generated files, vendored dependencies, secrets, large artifacts, and unrelated repositories before indexing broad workspace roots.
  • SafetyLocal filesReview MCP client configuration carefully when using an absolute project path in a global Claude Desktop config.
  • PrivacyLocal filesIndexed chunks, file paths, symbols, comments, Markdown, PDFs, configuration values, database files, daemon state, and search results can reveal proprietary source code and internal architecture.
  • PrivacyThird-party handlingEmbedding, reranking, LLM, and web search providers may receive code-derived queries or snippets if configured.
  • PrivacyCredentials & tokensLocal ChunkHound database files, logs, daemon state, and MCP transcripts may retain code-derived context after the session ends.
  • PrivacyCredentials & tokensAvoid sharing ChunkHound databases, config files with API keys, verbose logs, research outputs, and screenshots from private repositories.

Disclosure: MIT-licensed open-source codebase intelligence MCP server. Review provider configuration before enabling semantic search, LLM research, reranking, or web search features in sensitive repositories.

Safety notes

  • ChunkHound reads source files, Markdown, text, PDFs, and supported config files under the target directory and stores indexed chunks in a local database.
  • Realtime indexing and daemon mode can continue watching project files after the initial MCP connection.
  • Code research and web search tools require embedding, reranking, and LLM configuration and may invoke local CLIs or external model APIs depending on settings.
  • Exclude generated files, vendored dependencies, secrets, large artifacts, and unrelated repositories before indexing broad workspace roots.
  • Review MCP client configuration carefully when using an absolute project path in a global Claude Desktop config.

Privacy notes

  • Indexed chunks, file paths, symbols, comments, Markdown, PDFs, configuration values, database files, daemon state, and search results can reveal proprietary source code and internal architecture.
  • Embedding, reranking, LLM, and web search providers may receive code-derived queries or snippets if configured.
  • Local ChunkHound database files, logs, daemon state, and MCP transcripts may retain code-derived context after the session ends.
  • Avoid sharing ChunkHound databases, config files with API keys, verbose logs, research outputs, and screenshots from private repositories.

Prerequisites

  • Python 3.10 or newer and the `uv` package manager.
  • A local repository or workspace you are authorized to index.
  • ChunkHound JSON config reviewed for database path, excludes, embeddings, and LLM provider settings.
  • Optional embedding provider credentials for semantic search, or regex-only usage when no embedding key is configured.
  • Optional LLM provider or local CLI reviewed before enabling `code_research`.

Schema details

Install type
cli
Troubleshooting
No
Source repository stats
Scope
Source repo
Collection metadata
Estimated setup
15 minutes
Difficulty
advanced
Tool listing metadata
Disclosure
MIT-licensed open-source codebase intelligence MCP server. Review provider configuration before enabling semantic search, LLM research, reranking, or web search features in sensitive repositories.
Full copyable content
{
  "mcpServers": {
    "chunkhound": {
      "command": "chunkhound",
      "args": ["mcp"]
    }
  }
}

About this resource

Content

ChunkHound MCP Server connects Claude to a local-first codebase intelligence index. It parses repositories with tree-sitter, stores searchable chunks in DuckDB, and exposes MCP tools for code search, daemon status, deep code research, and optional web-backed research.

Use it when Claude needs targeted context from a large repository without reading broad files repeatedly. Regex search can work without embedding keys, while semantic search and research workflows depend on the embedding, reranking, and LLM providers configured in .chunkhound.json or environment variables.

Source Review

These sources were reviewed on 2026-06-06. Prefer the live repository, CLI reference, PyPI metadata, README, license, package metadata, configuration docs, MCP tool registry, stdio server, and MCP CLI command source for current setup and behavior.

Features

  • Run a stdio MCP server with chunkhound mcp.
  • Index local repositories into a DuckDB-backed code intelligence database.
  • Parse many programming, configuration, Markdown, text, and PDF formats.
  • Search code with semantic search when embeddings are configured.
  • Search with regex when no embedding provider is available.
  • Use realtime indexing and daemon mode for active repositories.
  • Inspect daemon status through MCP.
  • Run code_research when embeddings, reranking, and an LLM provider are configured.
  • Configure VoyageAI, OpenAI, local-compatible embeddings, DuckDB, LanceDB evaluation mode, indexing excludes, and LLM providers.

Installation

Install ChunkHound with uv:

uv tool install chunkhound

Create a project-local .chunkhound.json, then index the repository:

chunkhound index

Start the MCP server from the project:

chunkhound mcp

Configure Claude or another MCP client:

{
  "mcpServers": {
    "chunkhound": {
      "command": "chunkhound",
      "args": ["mcp"]
    }
  }
}

Use an explicit project path only when the global MCP client configuration must launch ChunkHound outside the repository directory.

Use Cases

  • Ask Claude to find authentication, routing, migration, or error-handling code across a large repository.
  • Run regex searches against indexed files when semantic embeddings are not configured.
  • Keep a local code index updated while switching branches.
  • Scope search to an approved repository instead of exposing a whole workspace.
  • Use code_research for higher-level architecture questions when the LLM and reranking providers are approved.

Safety and Privacy

ChunkHound is local-first, but it still creates a derived index of source code. Limit the target path, configure excludes, and verify what will be indexed before connecting a model to private repositories. Keep .chunkhound databases, logs, API keys, MCP transcripts, and research outputs out of public commits.

Semantic search, reranking, LLM research, and web search can involve external providers depending on configuration. Review every provider endpoint, model, API key, timeout, and custom base URL before enabling those features for sensitive codebases.

Duplicate Check

No chunkhound/chunkhound, ChunkHound MCP Server, chunkhound mcp, or matching source URL entry was found in content/mcp or README.md. Existing code index and codebase memory entries cover different projects; this entry documents ChunkHound's local-first tree-sitter, DuckDB, realtime indexing, and code_research MCP workflow.

Source citations

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How it compares

ChunkHound MCP Server side by side with 3 alternatives on trust, install, platform support, and disclosed safety notes — all from reviewed registry metadata.

1 trust signal differ across this comparison (Submitter).

Field

Local-first codebase intelligence MCP server that indexes repositories with tree-sitter, stores searchable chunks in DuckDB, and gives Claude semantic search, regex search, daemon status, and deep code research tools.

Open dossier

Local code indexing MCP server that lets AI assistants search repositories, build symbol indexes, inspect file summaries, monitor changes, and navigate multi-language codebases.

Open dossier

Code intelligence MCP server with a Zig core for local project indexing, structural outlines, symbol lookup, search, dependency graphs, snapshots, remote public-repo queries, and fallback edits.

Open dossier

Index any documentation — websites, GitHub repos, npm/PyPI packages, local files — and give Claude always-current, version-specific answers with the open-source Grounded Docs MCP server. An offline-first alternative to Context7, Nia, and Ref.Tools.

Open dossier
Next steps
Trust
Review statusNot reviewedNot reviewedNot reviewedNot reviewed
Package trustPackage not verifiedPackage not verifiedPackage not verifiedPackage not verified
Source provenanceSource-backedSource-backedSource-backedSource-backed
SubmitterDiffersoktofeesh1oktofeesh1oktofeesh1
Install riskReview firstReview firstReview firstReview first
Notes Safety ✓ Privacy ✓ Safety ✓ Privacy ✓ Safety ✓ Privacy ✓ Safety ✓ Privacy ✓
BrandChunkHound logoChunkHoundCodeDB logoCodeDB
Categorymcpmcpmcpmcp
SourceSource-backedSource-backedSource-backedSource-backed
AuthorChunkHoundjohnhuang316justracharabold
Added2026-06-062026-06-062026-06-062026-06-18
Platforms
Harness
Source repo
Safety notesChunkHound reads source files, Markdown, text, PDFs, and supported config files under the target directory and stores indexed chunks in a local database. Realtime indexing and daemon mode can continue watching project files after the initial MCP connection. Code research and web search tools require embedding, reranking, and LLM configuration and may invoke local CLIs or external model APIs depending on settings. Exclude generated files, vendored dependencies, secrets, large artifacts, and unrelated repositories before indexing broad workspace roots. Review MCP client configuration carefully when using an absolute project path in a global Claude Desktop config.Code Index MCP reads repository files, builds shallow and deep indexes, exposes file summaries, and can return source snippets through search and file resources. Point `--project-path` at one approved repository; avoid broad parent directories, home directories, generated dependency trees, or secret-heavy paths. Deep indexing and watcher refreshes can consume CPU, memory, disk IO, and temp storage on large codebases. The server can create and clear index/cache settings and temporary directories used for stored index data. Search results, file summaries, and symbol bodies can surface credentials, private code, customer data, internal URLs, or proprietary implementation details if they exist in the repository.CodeDB indexes local projects and exposes file tree, outline, search, symbol, caller, dependency, read, snapshot, project, and context tools to the MCP client. CodeDB's `codedb_edit` tool exists as a fallback editing tool and can create, replace, insert, delete, or modify files when used by a client without native edit tooling. The npm package runs a postinstall step that downloads a native binary from GitHub Releases; review package and release provenance in environments that restrict native binaries. Remote repo queries use the public `api.wiki.codes` service and should be treated as network access outside the local repository. The upstream README marks the project as alpha software, with parser coverage and snapshot formats still stabilizing.The server stores its index locally, but MCP tool arguments and returned search/fetch results can be visible to your MCP client and model provider transcript. The `scrape_documentation` and `fetch_url` tools can fetch URLs, GitHub repos, packages, or local paths — only index sources you are authorized to access and constrain local paths and network targets.
Privacy notesIndexed chunks, file paths, symbols, comments, Markdown, PDFs, configuration values, database files, daemon state, and search results can reveal proprietary source code and internal architecture. Embedding, reranking, LLM, and web search providers may receive code-derived queries or snippets if configured. Local ChunkHound database files, logs, daemon state, and MCP transcripts may retain code-derived context after the session ends. Avoid sharing ChunkHound databases, config files with API keys, verbose logs, research outputs, and screenshots from private repositories.Tool calls may expose file paths, filenames, source code snippets, imports, classes, methods, functions, symbols, search matches, complexity summaries, and project settings. Index data and temp directories can persist derived repository structure or symbol metadata outside the source tree. File watcher status, exclude patterns, and settings can reveal local project layout and development conventions. If an MCP client forwards tool results to a model provider, repository contents and search snippets may leave the local machine. Exclude secrets, generated artifacts, vendored dependencies, build output, and private data before indexing.Local indexes, snapshots, file trees, symbol names, dependency graphs, snippets, read results, and search results can reveal proprietary code structure and implementation details. Upstream documents sensitive-file blocking for patterns such as environment files, credentials, and keys, but users should still review ignore rules and avoid indexing secret-heavy directories. CodeDB writes telemetry to `~/.codedb/telemetry.ndjson` unless `CODEDB_NO_TELEMETRY=1` is set, then syncs aggregate tool counts, latency, startup, file count, line count, language, version, and platform data on MCP session close. Upstream telemetry docs state that source code, file contents, file paths, and search queries are not collected. Remote public-repo queries and local MCP responses may still be logged by MCP clients, model providers, and terminal history.Indexed documentation, local file contents, URLs, search queries, extracted text, and search results may be exposed to Claude or another MCP client when tools are invoked. Scraped content (HTML, Markdown, PDF, Office documents, source code) is stored in a local SQLite database on your machine; avoid indexing secrets, private repositories, internal URLs, or sensitive folders unless you intend them to be available through MCP results.
Prerequisites
  • Python 3.10 or newer and the `uv` package manager.
  • A local repository or workspace you are authorized to index.
  • ChunkHound JSON config reviewed for database path, excludes, embeddings, and LLM provider settings.
  • Optional embedding provider credentials for semantic search, or regex-only usage when no embedding key is configured.
  • Python 3.10 or newer.
  • uv or another Python package runner that can install `code-index-mcp`.
  • An approved repository path that the MCP client is allowed to inspect.
  • Optional native search tools such as ripgrep, ugrep, ag, or grep for faster search backends.
  • macOS or Linux on x64 or arm64 for the published native binary launcher.
  • Node.js 18 or newer when using the `codedeebee` npm launcher.
  • A local project directory that the MCP client exposes through roots or launches from.
  • Review of which local repositories, file types, generated artifacts, and secrets patterns may be indexed.
  • Node.js 22+ with `npx` available.
  • Start the server with `npx @arabold/docs-mcp-server@latest` before connecting — it listens at http://localhost:6280.
  • An MCP client such as Claude Code or Claude Desktop.
Install
uv tool install chunkhound
uvx code-index-mcp --project-path ABSOLUTE_PATH_TO_REPOSITORY
npx -y codedeebee mcp
claude mcp add --transport http docs-mcp http://localhost:6280/sse
Config
{
  "mcpServers": {
    "chunkhound": {
      "command": "chunkhound",
      "args": ["mcp", "/path/to/approved/project"]
    }
  }
}
Manual-only setup:
uvx code-index-mcp --project-path ABSOLUTE_PATH_TO_REPOSITORY
{
  "mcpServers": {
    "codedb": {
      "command": "npx",
      "args": [
        "-y",
        "codedeebee",
        "mcp"
      ],
      "type": "stdio"
    }
  }
}
{
  "mcpServers": {
    "docs-mcp-server": {
      "type": "sse",
      "url": "http://localhost:6280/sse"
    }
  }
}
Citations
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