Library Context Protocol

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

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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.

On niche and post-cutoff Python libraries, the shipped LCP plugin lifts a small model's task success rate from 28% to 66% and halves its API-misuse rate — beating, on task success, an agent that reads the installed source. Full reproducible methodology and per-run data: Benchmark.

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

When to choose LCP

Choose LCP when your AI agent needs exact, offline ground truth about the library versions installed in your environment — including private packages that no documentation service has ever seen. Choose a service like Context7 when you want curated narrative documentation (tutorials, guides) for popular public libraries: LCP does not compete on prose, it competes on being provably right about your environment.

	LCP	Context7	llms.txt	Reading site-packages
Matches the installed version	yes	no	no	yes
Works offline	yes	no	no	yes
Private / internal packages	yes	no	no	yes
Token-dense structured answers	yes	narrative text	coarse summary	raw source (expensive)

See the full comparison in the docs.

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

# Universal server: resolves any installed library on demand
lcp serve-all

# Restrict and pre-warm specific libraries
lcp serve-all --expose requests --preload requests

MCP Client Configuration

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

{
  "mcpServers": {
    "lcp": {
      "command": "lcp",
      "args": ["serve-all"]
    }
  }
}

Available MCP Tools

Tool	Description
resolve_library(name, version?)	Load a library (cache → live scan → registry). Call first.
search(query, library?, module?, kind?, limit?)	Ranked symbol search; empty query browses. Hits include the exact import line.
get_symbol(ids, library?)	Batch detail: full signatures, parameters, import lines; classes inline member summaries.
get_overview(library?)	Library identity plus the module tree with symbol counts.

Programmatic Usage

from lcp.mcp_server import create_universal_server

server = create_universal_server(name="my-server", preload=["requests"])
server.run()  # serve on stdio

# Or invoke tools in-process, without the MCP protocol
server.tools["search"]("send get request", library="requests")

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-config.json — per-project configuration

The plugin uses a .lcp-config.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. Earlier versions named this file .lcp.json; the old name still works as a deprecated fallback — rename it to .lcp-config.json.

Locations (first found wins):

• ${CLAUDE_PROJECT_DIR}/.lcp-config.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-config.json-only fields (not in userConfig).

To change an option: edit .lcp-config.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-config.json → command
2. .lcp-config.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