clichefactory-mcp 0.1.0

MCP server for ClicheFactory — structured data extraction from documents

clichefactory-mcp

MCP (Model Context Protocol) server for ClicheFactory — structured data extraction from documents.

This server exposes ClicheFactory's extraction and document conversion capabilities as MCP tools, allowing AI assistants in Cursor, Claude Desktop, OpenClaw, and other MCP-compatible clients to extract structured data from PDFs, images, DOCX, XLSX, CSV, EML, and more.

Tools

Tool	Description
extract	Extract structured JSON from a document using a schema
to_markdown	Convert a document to markdown text
doctor	Check configuration, dependencies, and system binaries

extract

The main tool. Pass a document file and a JSON schema — get structured data back.

Supports all extraction modes:

Mode	Description	Requires
(default)	OCR + LLM extraction	local: LLM key · service: API key
fast	Fastest pipeline	Same as default
trained	Trained pipeline artifact	Service + artifact_id
robust	Two-stage extract + verify	Service only
robust-trained	Trained extract + verification	Service + artifact_id

The schema can be provided as:

• File path: absolute path to a .json schema file
• Inline dict: the LLM constructs a JSON schema from the conversation (e.g., the user says "extract the invoice number and total" and the LLM builds {"type": "object", "properties": {"invoice_number": {"type": "string"}, "total": {"type": "number"}}})

to_markdown

Converts any supported document to markdown. Useful for inspecting document contents or feeding them to the LLM for analysis before deciding on an extraction schema.

doctor

Runs diagnostics on the ClicheFactory setup — config file, API keys, Python dependencies, system binaries. Call this when things aren't working.

Execution Modes

The server supports two modes, matching the SDK and CLI:

• local — Runs extraction on your machine. You bring your own LLM key (BYOK). Supports Gemini, OpenAI, Anthropic, and Ollama models. Requires the clichefactory[local] dependencies for document parsing.

• service — Uses the ClicheFactory cloud service. Requires a ClicheFactory API key. Supports all extraction modes including trained pipelines and robust verification. Optionally accepts BYOK model overrides.

Installation

Prerequisites

• Python ≥ 3.12
• uv (recommended) or pip

From PyPI

pip install clichefactory-mcp

For local-mode extraction (document parsing on your machine), install with the local extras:

pip install "clichefactory-mcp[local]"

Configuration

Environment Variables

Set these in your MCP client configuration (see below) or in ~/.clichefactory/config.toml via clichefactory configure.

Variable	Required	Description
CLICHEFACTORY_API_KEY	Service mode	ClicheFactory API key (format: cliche-...)
CLICHEFACTORY_API_URL	No	Service URL override (default: production)
LLM_MODEL_NAME	Local mode	Model name, e.g. gemini/gemini-3-flash-preview
LLM_API_KEY	Local mode	API key for the LLM provider
OCR_MODEL_NAME	No	Separate OCR/VLM model (defaults to main model)
OCR_API_KEY	No	API key for OCR model (defaults to main key)

The config file at ~/.clichefactory/config.toml (created by clichefactory configure) is also respected. Environment variables take precedence over the config file.

Cursor

Add to .cursor/mcp.json in your project (or global Cursor settings):

{
  "mcpServers": {
    "clichefactory": {
      "command": "uv",
      "args": ["--directory", "/absolute/path/to/cliche-mcp", "run", "clichefactory-mcp"],
      "env": {
        "LLM_MODEL_NAME": "gemini/gemini-3-flash-preview",
        "LLM_API_KEY": "your-gemini-api-key"
      }
    }
  }
}

For service mode:

{
  "mcpServers": {
    "clichefactory": {
      "command": "uv",
      "args": ["--directory", "/absolute/path/to/cliche-mcp", "run", "clichefactory-mcp"],
      "env": {
        "CLICHEFACTORY_API_KEY": "cliche-your-key-here",
        "CLICHEFACTORY_API_URL": "https://api.clichefactory.com"
      }
    }
  }
}

Claude Desktop

Add to ~/Library/Application Support/Claude/claude_desktop_config.json (macOS) or %APPDATA%\Claude\claude_desktop_config.json (Windows):

{
  "mcpServers": {
    "clichefactory": {
      "command": "uv",
      "args": ["--directory", "/absolute/path/to/cliche-mcp", "run", "clichefactory-mcp"],
      "env": {
        "LLM_MODEL_NAME": "gemini/gemini-3-flash-preview",
        "LLM_API_KEY": "your-gemini-api-key"
      }
    }
  }
}

OpenClaw

Register the MCP server with your OpenClaw agent:

openclaw mcp set clichefactory '{"command":"uv","args":["--directory","/absolute/path/to/cliche-mcp","run","clichefactory-mcp"],"env":{"LLM_MODEL_NAME":"gemini/gemini-3-flash-preview","LLM_API_KEY":"your-gemini-api-key"}}'

For service mode:

openclaw mcp set clichefactory '{"command":"uv","args":["--directory","/absolute/path/to/cliche-mcp","run","clichefactory-mcp"],"env":{"CLICHEFACTORY_API_KEY":"cliche-your-key-here","CLICHEFACTORY_API_URL":"https://api.clichefactory.com"}}'

Verify with openclaw mcp list. The agent can now use extract, to_markdown, and doctor tools in any conversation.

An OpenClaw skill with agent instructions is also available in integrations/openclaw/. To install it into your workspace:

cp -r /path/to/cliche-mcp/integrations/openclaw ~/.openclaw/skills/clichefactory

Or, once published to ClawHub:

openclaw skills install clichefactory

When published on PyPI

Once clichefactory-mcp is on PyPI, replace the command in any of the above configurations with uvx:

Cursor / Claude Desktop:

{
  "mcpServers": {
    "clichefactory": {
      "command": "uvx",
      "args": ["clichefactory-mcp"],
      "env": {
        "LLM_MODEL_NAME": "gemini/gemini-3-flash-preview",
        "LLM_API_KEY": "your-gemini-api-key"
      }
    }
  }
}

OpenClaw:

openclaw mcp set clichefactory '{"command":"uvx","args":["clichefactory-mcp"],"env":{"LLM_MODEL_NAME":"gemini/gemini-3-flash-preview","LLM_API_KEY":"your-gemini-api-key"}}'

Supported File Types

PDF, PNG, JPG, JPEG, WebP, GIF, BMP, DOCX, DOC, ODT, XLSX, CSV, EML, TXT, MD.

Differences from the CLI

This MCP server covers the core extraction and conversion workflows. The following CLI features are not included in v1:

Feature	Reason
Batch operations (extract-batch, to-markdown-batch)	MCP tools are typically called one-at-a-time by the LLM. For multiple documents, the LLM calls extract in sequence. Batch support may be added in a future version.
configure	Interactive prompts don't work in MCP. Use env vars or run clichefactory configure in a terminal.
--output / -o flag	MCP tools return results directly to the LLM rather than writing to files.
allow_partial	Not exposed as a tool parameter in v1.
OCR engine selection	Uses the SDK defaults (RapidOCR). Configure via ~/.clichefactory/config.toml or pass parsing options through the SDK if needed.

Development

# Install in development mode
uv sync

# Run the server directly (stdio transport, for testing with MCP clients)
uv run clichefactory-mcp

# Inspect available tools (requires mcp CLI)
uv run mcp dev cliche_mcp/server.py

License

MIT — Copyright (c) 2026 Urban Susnik s.p.