LLMScribe
Turn any code repository into clean, structured, deterministic data. No AI. No embeddings. No hidden ranking. Open source and available as a free hosted MCP.
Pst. Hey, you, join our stargazers :)
Why LLMScribe?
- Deterministic: Same input, predictable output. No LLM, embeddings, or AI ranking
- Repository-first: Works with local projects and public GitHub repositories, no cloning required
- Structured output: Machine-readable JSON for every operation
- Fast discovery: Map a project, search it, then retrieve exactly what you need
- Dependency-aware: Understand local, external, and unresolved dependencies
- Git-aware: Inspect status and unified diffs
- Agent ready: Connect LLMScribe to any AI agent or MCP client with a single config block
- Multiple interfaces: CLI, MCP, GUI, and a programmatic core, all sharing the same engine
- Open source: Apache-2.0, self-hostable, and free forever
LLMScribe doesn't try to be the intelligence. It provides the data that intelligence needs.
Feature Overview
Core Tools
| Feature | Description |
|---|---|
| Map | Generate a clean directory tree without dumping file contents |
| Search | Search file paths, file names, file contents, and individual lines |
| Read | Safely retrieve a specific file |
More
| Feature | Description |
|---|---|
| Read Many | Retrieve multiple files in a single operation |
| Dependencies | See what a file depends on and what depends on it |
| Diff | Inspect Git status and unified diffs |
| Overview | Export the complete structure and supported file contents |
Quick Start
Install LLMScribe from PyPI:
pip install llmscribe
Then point it at any project directory, or (through the MCP tools) at a public GitHub repo. No API key needed.
The
project_map(...),search(...),read(...)snippets below show MCP tool calls. The same operations are available from the CLI (local directories) and from Python throughllmscribe.core(see Python API).
Map
Generate a clean directory tree without file contents. This is the best first step when exploring an unfamiliar repository.
project_map()
# or a public GitHub repo, no clone needed
project_map(repo="owner/repo")
CLI / MCP
CLI
llmscribe map
llmscribe map --json
MCP
project_map
Output:
src/
├── api/
│ ├── routes.py
│ └── auth.py
├── models/
│ └── user.py
└── main.py
Search
Search across file paths, file names, file contents, and individual lines. Search is intentionally deterministic: LLMScribe does not try to guess what you meant.
search(query="authentication")
# or a public GitHub repo
search(query="authentication", repo="owner/repo")
CLI / MCP
CLI
llmscribe search "authentication"
llmscribe search "authentication" --json
MCP
search
Each match includes the file path, line number, the matching line, the matched text and the match type (filename or content). Results are ordered by path then line and limited to 1,000 matches; binary and oversized files are skipped.
Output (--json, data.matches):
[
{
"file_path": "src/auth/service.py",
"line_number": 12,
"line_content": "def authenticate(user, password):",
"match_type": "content",
"matched_text": "authenticate"
}
]
Read
Safely retrieve the contents of a specific file. LLMScribe validates paths and prevents path traversal outside the project.
read(file_path="src/auth/service.py")
# or a public GitHub repo
read(file_path="src/main.py", repo="owner/repo")
CLI / MCP
CLI
llmscribe read src/auth/service.py
MCP
read
pathandrepoare mutually exclusive. Usepathfor a local project andrepofor a public GitHub repository.
Power Your Agent
Instead of throwing an entire repository into a context window, an agent can progressively retrieve exactly what it needs:
1. project_map()
↓
2. search("authentication")
↓
3. read("src/auth/service.py")
↓
4. project_dependencies("src/auth/service.py")
↓
5. read_many([...])
MCP
Connect any MCP-compatible client (Cursor, Claude, Windsurf, and more) to your repository.
Free hosted MCP. No installation required:
{
"mcpServers": {
"llmscribe": {
"url": "https://llmscribe.onrender.com/mcp"
}
}
}
For clients that support custom remote connectors, simply provide the endpoint: https://llmscribe.onrender.com/mcp
The public endpoint is convenient for experimentation. For private code or production workloads, self-host LLMScribe instead.
Local MCP. Runs on your machine, over stdio:
{
"mcpServers": {
"llmscribe": {
"command": "llmscribe-mcp"
}
}
}
Alternative: Python module
{
"mcpServers": {
"llmscribe": {
"command": "python",
"args": ["-m", "llmscribe.mcp"]
}
}
}
Available tools
project_map
project_overview
search
read
read_many
project_dependencies
project_diff
More Tools
Read Many
Retrieve multiple files in a single operation. Partial success is supported, so one problematic file does not invalidate the entire request.
read_many([
"src/auth/service.py",
"src/auth/models.py",
"src/api/login.py"
])
llmscribe read-many src/auth/service.py src/api/login.py
Dependencies
Inspect the dependency relationships around a file. LLMScribe identifies local dependencies, external dependencies, unresolved dependencies, and the files that depend on this file.
project_dependencies("src/auth/service.py")
llmscribe dependencies src/auth/service.py --json
Output:
src/auth/service.py
│
├── depends on
│ ├── auth/models.py
│ ├── auth/config.py
│ └── auth/utils.py
│
└── used by
├── api/login.py
└── tests/test_auth.py
This is particularly useful when determining the potential impact of modifying a file.
Diff
Inspect repository changes using Git. Supports Git status, unstaged changes, staged changes, specific commits, and unified diffs.
llmscribe diff
This lets applications and agents understand not only the current repository, but also what changed.
Overview
Generate a complete project snapshot containing the directory structure, supported text file contents, and structured project information.
llmscribe overview
Best for small and medium-sized projects. For large repositories, use the recommended workflow instead:
map → search → read
CLI
Every command can return machine-readable JSON with --json, which makes the CLI a building block for scripts, automation, and developer tools.
llmscribe map
llmscribe overview
llmscribe search "authentication"
llmscribe read src/auth/service.py
llmscribe read-many src/auth/service.py src/api/login.py
llmscribe dependencies src/auth/service.py
llmscribe diff
# machine-readable output
llmscribe map --json
llmscribe search "auth" --json
llmscribe dependencies src/auth/service.py --json
Self-Hosting
Run your own HTTP MCP server for private repositories, teams, internal developer tools, and production applications.
Run locally
pip install llmscribe
MCP_TRANSPORT=http MCP_ALLOW_LOCAL_PATHS=1 llmscribe-mcp
The server will be available at http://localhost:8000/mcp, with GET /health and GET /info for monitoring.
Over HTTP the
pathargument is disabled by default so a hosted server does not expose its own disk. SetMCP_ALLOW_LOCAL_PATHS=1to allow any local path (only on a machine you trust), orMCP_ALLOWED_ROOTS=/srv/a:/srv/bto allow specific directories. GitHub repositories (repo=) always work.
Docker
docker build -t llmscribe-mcp .
docker run -p 8000:8000 -e MCP_ALLOWED_HOSTS="localhost,localhost:*,mcp.example.com" llmscribe-mcp
The image runs python -m llmscribe.mcp with MCP_TRANSPORT=http, as an unprivileged user, and has a /health with a healthcheck.
Railway
railway up
Environment Variables
| Variable | Description | Default |
|---|---|---|
MCP_TRANSPORT |
stdio or http |
stdio |
HOST |
HTTP bind address | 0.0.0.0 |
PORT |
HTTP port | 8000 |
MCP_ALLOWED_HOSTS |
Accepted Host values for /mcp (comma-separated, host:* for any port, * for any). Default: loopback plus RENDER_EXTERNAL_HOSTNAME / RAILWAY_PUBLIC_DOMAIN |
loopback |
MCP_ALLOWED_ORIGINS |
Accepted Origin values for /mcp (requests without an Origin, i.e. all non-browser clients, are always accepted). Default: loopback, claude.ai, the platform hostname; * allows any |
see left |
MCP_ALLOW_LOCAL_PATHS |
1 allows any local path over HTTP |
off |
MCP_ALLOWED_ROOTS |
Directories (separated by : / ;) allowed as path over HTTP |
none |
GITHUB_TOKEN / GH_TOKEN |
Token for private repositories and higher rate limits (sent only to api.github.com) |
none |
LLMSCRIBE_CACHE_MAX_ENTRIES |
GitHub snapshots kept in memory (0 disables) |
8 |
LLMSCRIBE_CACHE_TTL_SECONDS |
Snapshot lifetime | 300 |
Run a single process (the cache and MCP sessions live in memory). PORT without MCP_TRANSPORT still selects HTTP for backward compatibility, but set MCP_TRANSPORT=http explicitly.
Python API
from pathlib import Path
from llmscribe.core import project_map, search_project, read_file, read_files, analyze_dependencies, get_git_diff, LLMScribeError
root = Path(".")
print(project_map(root).tree)
print(search_project("auth", root).to_dict())
print(read_files(["README.md", "missing.py"], root).to_dict()) # per-file errors, never raises
try:
analyze_dependencies("src/app.py", root)
except LLMScribeError as err: # err.code is a stable machine-readable code
print(err.code, err.message)
Behavior reference
Ignore rules. Defaults (.git, node_modules, venv, dist, build, .env, *.log, …), the root .gitignore and nested .gitignore files are applied with real Git semantics (wildcards, directories, ! negation, root-anchored patterns). Hidden files are included unless ignored; symlinks are never followed or listed.
Supported text files. Known source/config/doc extensions plus names such as Dockerfile, Makefile, LICENSE, .gitignore. Other files appear in the tree but cannot be read or searched.
Limits (single source: llmscribe.core.limits): 400,000 content characters per overview/read_many, 50 files per read_many, 1,000 search matches, 20,000 map entries, 2 MiB per file, 200,000 diff characters, 100 MiB archive download, 250 MiB / 100,000 entries per archive. Anything cut is reported (truncated, truncation_note, omitted_files).
Errors. Every failure has a stable code: invalid_argument, invalid_path, file_not_found, unsupported_file_type, binary_file, file_too_large, read_error, repository_not_found, not_a_repository, repository_too_large, github_rate_limited, github_auth_required, github_unavailable, git_unavailable, unsupported_operation, internal_error. JSON: {"ok": false, "tool": "...", "error": {"code": "...", "message": "..."}}.
Dependencies. Python, JavaScript/TypeScript, Java, Go, Rust, C/C++. Each reference is local, stdlib, external (not in the repository, assumed third-party) or unresolved (relative/local reference that matches nothing); used_by lists reverse dependencies. Works identically for local and GitHub sources.
GitHub. Public repositories (and private ones with GITHUB_TOKEN) are fetched as one zip archive and cached in memory per owner/repo/ref/credential. Nothing is cloned or written to disk. project_diff on GitHub uses the compare API and requires commit (base) with optional ref (head); staged is local only.
Git diff (local). Runs git with an argument list, a 30 s timeout, a minimal environment, and without external diff/textconv drivers.
Migration notes
- Legacy tool names (
project_get_file,project_get_files,project_search,project_list_files) are gone; useread,read_many,search. - Error code
path_traversalis nowinvalid_path;not_text_fileisunsupported_file_type. project_dependenciesresults:all_local_files/all_external_deps/all_unresolvedwere replaced byused_byand per-category lists (stdlib_dependenciesadded).llmscribe.corefunctions raiseLLMScribeError(notFileNotFoundError) for a bad root; the dependency-provider classes andllmscribe.github.providerhelpers were removed.- Over HTTP, local
pathaccess now requiresMCP_ALLOW_LOCAL_PATHSorMCP_ALLOWED_ROOTS.
Architecture
All interfaces share one core engine, so behavior stays consistent everywhere.
Repository
│
┌─────────────┴─────────────┐
│ │
Local Project GitHub Repo
│ │
└─────────────┬─────────────┘
▼
LLMScribe Core
│
┌─────────────────────┼─────────────────────┐
│ │ │
▼ ▼ ▼
CLI MCP GUI
│ │
└──────────────┬──────┘
▼
Structured Output
/ JSON
Philosophy
LLMScribe intentionally stays simple. The goal is not to make the repository "smarter." The goal is to make the repository accessible to software.
We provide
- Repository extraction
- Deterministic search
- Structured project data
- File retrieval
- Dependency information
- Git information
- Multiple interfaces
We don't provide
- ❌ AI-generated answers
- ❌ Embedding-based search
- ❌ Semantic ranking
- ❌ Autonomous coding
- ❌ An AI coding agent
- ❌ A generic Git client
Use Cases
- AI coding agents
- MCP applications
- Developer tools
- Code search interfaces
- Repository explorers
- Documentation systems
- Code analysis pipelines
- Automation scripts
- Local LLM applications
- Exploring unfamiliar open-source projects
Open Source vs Hosted
LLMScribe is open source under the Apache License 2.0. Run it locally, inspect the source, modify it, self-host it, and build your own integrations.
The hosted MCP endpoint provides a convenient zero-install option for trying it out, while the open-source project gives you complete control.
Resources
- Website: https://llmscribe.vercel.app
- GitHub: https://github.com/AMRITO-KUNDU/llmscribe
- PyPI: https://pypi.org/project/llmscribe/
- Public MCP: https://llmscribe.onrender.com/mcp
- Issues: https://github.com/AMRITO-KUNDU/llmscribe/issues
- Contributing: https://github.com/AMRITO-KUNDU/llmscribe/blob/main/CONTRIBUTING.md
Contributing
Contributions are welcome. If you want to improve repository extraction, search, dependency analysis, interfaces, integrations, or documentation, check the contributing guide before opening a pull request.
License
LLMScribe is licensed under the Apache License 2.0. See the LICENSE file for details.
Repository data, structured.
Metadata
Release files for llmscribe 1.2.1
For a detailed explanation of source distributions (sdists) and built distributions (wheels), please see the package formats documentation.
Source distribution (sdist)
| File | Size | Uploaded | |
|---|---|---|---|
| llmscribe-1.2.1.tar.gz | 73.0 kB | Details |
Built distribution (wheel)
| File | Interpreter | ABI | Platform | Reset |
|---|---|---|---|---|
| llmscribe-1.2.1-py3-none-any.whl | Python 3 | none | any | Details |
Total release size: 140.6 kB
Release files / llmscribe-1.2.1.tar.gz
| Download URL | llmscribe-1.2.1.tar.gz |
|---|---|
| Size | 73.0 kB |
| Tags | Source |
|
SHA-256 checksum How to use checksums |
6adb40b9a048aba12c9c86ce10902b427a218c9334bfbe62a1bf4f6c163ed839
|
|
BLAKE2b-256 checksum How to use checksums |
ae98c250db4259c35aee6b1247c0b747bc6055c9be8dede457a6eafff2233b78
|
| Upload date | |
|
Uploaded using Trusted Publishing? What is trusted publishing? |
Yes |
| Uploaded via |
twine/7.0.0 CPython/3.13.14
|
Provenance
Provenance describes where a file came from. On PyPI, provenance is shared via attestations, which provide a verifiable record of the build or publishing details. View details, limitations and caveats.
PyPI Publish Attestation
PyPI verified that this artifact, at this checksum, originated from the publisher listed below.
Signed by GitHub Actions, verified by PyPI on Oct 13, 2026.
Transparency logRelease files / llmscribe-1.2.1-py3-none-any.whl
| Download URL | llmscribe-1.2.1-py3-none-any.whl |
|---|---|
| Size | 67.6 kB |
| Tags | Python 3 |
|
SHA-256 checksum How to use checksums |
bee11b81718b621b0a053674f6e9186dfed792c70018aa8e1523876e17fc5eb8
|
|
BLAKE2b-256 checksum How to use checksums |
5b6d2fb1e629605a14032c9d01dfb2ded50a50f207fa2d058e7150bdc7229b50
|
| Upload date | |
|
Uploaded using Trusted Publishing? What is trusted publishing? |
Yes |
| Uploaded via |
twine/7.0.0 CPython/3.13.14
|
Provenance
Provenance describes where a file came from. On PyPI, provenance is shared via attestations, which provide a verifiable record of the build or publishing details. View details, limitations and caveats.
PyPI Publish Attestation
PyPI verified that this artifact, at this checksum, originated from the publisher listed below.
Signed by GitHub Actions, verified by PyPI on Oct 13, 2026.
Transparency log