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Library Context Protocol

Supported Python Versions PyPI version Tests Downloads License


Documentation: https://zazza123.github.io/lcp


lcp (Library Context Protocol) is primarly a protocol designed to solve the problem of AI agents not having access to up-to-date library documentation, which leads to hallucinations and inaccurate code generation. The LCP SDK provides tools to scan Python packages, extract API information, and generate LCP-compliant JSON manifests. It also includes features for analyzing documentation coverage and generating missing docstrings using AI.

Installation

pip install lcp

Features

  • Scans installed Python packages using inspect and ast modules
  • Generates LCP v1 compliant JSON files
  • Extracts functions, classes, methods, attributes, and constants
  • Parses docstrings for summaries and descriptions
  • Extracts type hints from function signatures
  • Validates output against LCP JSON schema
  • Documentation coverage analysis with JSON/Markdown reports
  • Version diff to detect deprecated symbols across releases
  • AI-powered docstring generation via OpenAI and Anthropic (lcp[ai])
  • Both CLI and Python API interfaces
  • MCP server for AI agent integration

Usage

CLI

# Scan a package and output LCP JSON
lcp scan requests -o requests.lcp.json

# Include private symbols
lcp scan mypackage --include-private

# Skip validation
lcp scan mypackage --no-validate

# Start an MCP server for a library manifest
lcp serve requests.lcp.json

Python API

from lcp import scan

# Scan a package
lcp_doc = scan("requests")

# Save to file
lcp_doc.to_file("requests.lcp.json")

# Get as dict
data = lcp_doc.to_dict()

# Include private symbols
lcp_doc = scan("mypackage", include_private=True)

Documentation Coverage

Analyze documentation completeness of a package to identify missing docstrings.

CLI

# Generate coverage report (JSON)
lcp coverage requests -o coverage.json

# Generate coverage report (Markdown)
lcp coverage requests -o coverage.md --format markdown

# Generate both LCP manifest and coverage report in one scan
lcp scan requests -o requests.lcp.json --coverage coverage.json

Python API

from lcp import generate_coverage

# Generate coverage report
report = generate_coverage("requests")

# Check coverage percentage
print(f"Coverage: {report.summary.coverage_percent}%")
print(f"Documented: {report.summary.documented}/{report.summary.total_symbols}")

# List undocumented symbols
for symbol in report.undocumented:
    print(f"  - {symbol.module}:{symbol.entity} ({symbol.kind})")

# Save report
report.to_file("coverage.json")      # JSON format
report.to_file("coverage.md")        # Markdown format

Version Diff

Compare two LCP manifests to detect symbols that were removed between versions and automatically generate deprecation entries.

CLI

# Compare two versions and print the diff report
lcp diff v1.lcp.json v2.lcp.json

# Save the diff report to a file
lcp diff v1.lcp.json v2.lcp.json -o diff.json

# Automatically update the new manifest with deprecation entries
lcp diff v1.lcp.json v2.lcp.json --update

Python API

from lcp import diff_documents, load_lcp_document, update_document

# Load two versions
old = load_lcp_document("v1.lcp.json")
new = load_lcp_document("v2.lcp.json")

# Compare
result = diff_documents(old, new)
print(f"Removed: {len(result.removed)}, Added: {len(result.added)}")

for sid, dep in result.deprecated.items():
    print(f"  {sid}: deprecated in {dep.deprecated_in}")

# Merge deprecations into the new document
updated = update_document(new, result)
updated.to_file("v2.lcp.json")

MCP Server

The SDK includes an MCP (Model Context Protocol) server that exposes LCP manifest data to AI agents. This allows agents to explore library APIs and generate accurate code.

Starting the Server

# Start MCP server for a library
lcp serve requests.lcp.json

# With custom server name
lcp serve numpy.lcp.json --name numpy-docs

MCP Client Configuration

Add to your MCP client configuration (e.g., Claude Desktop):

{
  "mcpServers": {
    "requests-api": {
      "command": "lcp",
      "args": ["serve", "/path/to/requests.lcp.json"]
    }
  }
}

Available MCP Tools

Tool Description
get_manifest Get library metadata (name, version, language)
list_modules List all modules in the library
list_symbols Browse symbols with optional filtering by module or kind
get_symbol Get full details for a specific symbol
search_symbols Find symbols by text search
get_class_members Get all methods and attributes of a class

Programmatic Usage

from lcp.mcp_server import create_server, run_server

# Create and customize server
server = create_server("path/to/manifest.lcp.json", name="my-server")

# Or run directly
run_server("path/to/manifest.lcp.json")

AI Documentation Generation

Automatically generate missing docstrings using LLM providers (OpenAI, Anthropic). Requires the optional ai extra:

pip install lcp[ai]

CLI

# Generate coverage report first
lcp coverage mypackage -o coverage.json

# Generate docstrings (dry-run to preview)
lcp docgen coverage.json --provider openai --dry-run

# Generate docstrings for real
lcp docgen coverage.json --provider openai

# Use Anthropic
lcp docgen coverage.json --provider anthropic --model claude-sonnet-4-20250514

# Filter by symbol kind
lcp docgen coverage.json --kinds class,function,method

# Provide a guiding description
lcp docgen coverage.json --description "A web framework for building REST APIs"

# Use OpenAI reasoning models (o1, o3)
lcp docgen coverage.json --provider openai --model o3 --reasoning

Python API

from lcp.ai import DocGenAgent, DocGenConfig, OpenAIProvider

# Create provider and agent
provider = OpenAIProvider(model="gpt-4o")
config = DocGenConfig(kinds=["class", "function"], dry_run=True)
agent = DocGenAgent(provider=provider, config=config)

# Run on a coverage JSON file
result = agent.run("coverage.json")

# Or pass a dict directly
result = agent.run(coverage_dict)

# Inspect results
print(f"Updated: {result.symbols_updated}")
print(f"Tokens: {result.total_usage.input_tokens} in / {result.total_usage.output_tokens} out")
for r in result.results:
    print(f"  {r.symbol_id}: {r.status}")

Claude Code Plugin

The SDK ships a ready-to-install Claude Code plugin in plugin/lcp/. It packages lcp serve-all as an MCP server so Claude Code can resolve any Python library on demand — including private packages installed in your project's virtualenv.

Install lcp first

lcp introspects packages by importing them in-process, so it must run inside the same Python environment as your project's dependencies. For live introspection of project packages, install it in your project virtualenv:

# Inside your project virtualenv
uv pip install lcp      # recommended with uv
pip install lcp         # plain pip

The plugin auto-detects .venv under your project root — no extra configuration needed for the common case.

For a global install (public libraries via the registry; does not see project-specific packages unless also globally installed):

pipx install lcp        # recommended
uv tool install lcp

Install the plugin

Add the marketplace and install the plugin in two slash commands:

/plugin marketplace add zazza123/lcp
/plugin install lcp@lcp

Once installed, Claude Code automatically starts the LCP MCP server on session start. The lcp-universal skill instructs the agent to call resolve_library("package") before writing code that depends on an external library.

For local development (when working on the plugin itself), load it directly instead:

claude --plugin-dir /path/to/lcp/plugin/lcp

.lcp.json — per-project configuration

The plugin uses a .lcp.json file to select the correct lcp launcher for each project. The SessionStart hook auto-generates this file when absent, seeding it from settings.json pluginConfigs values; edit the file directly thereafter.

Locations (first found wins):

  • ${CLAUDE_PROJECT_DIR}/.lcp.json — per-project (safe to check in)
  • ~/.lcp/config.json — global fallback

Schema (all fields optional):

{
  "command":    "/path/to/lcp",            // explicit lcp binary
  "python":     "/path/to/python",         // interpreter → `python -m lcp`
  "registries": ["https://..."],           // registry URLs → lcp serve-all --registry
  "expose":     ["fastapi", "pydantic"],   // allow-list; omitted/empty = expose all packages
  "preload":    ["fastapi"]                // packages resolved at server startup
}

command and python are mutually exclusive; command wins if both are set. expose and preload are .lcp.json-only fields (not in userConfig).

To change an option: edit .lcp.json directly. To reset from settings.json, delete the file and restart the session — the hook regenerates it from pluginConfigs.lcp@lcp.options.

Launcher resolution order

The wrapper probes each candidate with --version; the first that succeeds wins:

  1. .lcp.json → command
  2. .lcp.json → python → python -m lcp
  3. Auto-detected project venv under ${CLAUDE_PROJECT_DIR}: .venv/bin/lcp, .venv/bin/python -m lcp, venv/bin/lcp, venv/bin/python -m lcp
  4. Active virtualenv via $VIRTUAL_ENV: $VIRTUAL_ENV/bin/lcp, $VIRTUAL_ENV/bin/python -m lcp
  5. uv run --project <dir> --with lcp lcp if uv is present (ephemeral; layers lcp onto the project env)
  6. Global fallback: lcp on PATH → uvx lcp → pipx run lcp

If none resolve, the plugin emits an actionable message — never a bare -32000.

Shortcuts

Shortcut Action
/lcp:resolve <package> Resolve a library and summarise its public API
/lcp:scan <package> Scan a package and display module/symbol overview

License

MIT

Metadata

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