Unstructured API MCP Server

# Unstructured API MCP Server An MCP server implementation for interacting with the Unstructured API. This server provides tools to list sources and workflows. ## Setup 1. Install dependencies: - `uv add "mcp[cli]"` - `uv pip install --upgrade unstructured-client python-dotenv` or use `uv sync`. 2. Set your Unstructured API key as an environment variable. - Create a `.env` file in the root directory, and add a line with your key: `UNSTRUCTURED_API_KEY="YOUR_KEY"` To test in local, any working key that pointing to prod env would work. However, to be able to return valid results from client's side (e.g, Claude for Desktop), your personal key that is fetched from `https://platform.unstructured.io/app/account/api-keys` is needed. ## Running the Server Using the MCP CLI: ```bash mcp run server.py ``` or: ```bash uv run server.py ``` ## Available Tools ### Sources #### list_sources Lists available sources from the Unstructured API. Parameters: - `source_type` (optional): Filter sources by connector type #### get_source_info Get detailed information about a specific source connector. Parameters: - `source_id`: ID of the source connector to get information for #### create_s3_source Create an S3 source connector. Parameters: - `name`: Unique name for the connector - `remote_url`: S3 URI to the bucket or folder (e.g., s3://my-bucket/) - `key` (optional): AWS access key ID (required if not using anonymous auth) - `secret` (optional): AWS secret access key (required if not using anonymous auth) - `token` (optional): AWS STS session token for temporary access - `anonymous` (optional): Whether to use anonymous authentication (default: false) - `endpoint_url` (optional): Custom URL if connecting to a non-AWS S3 bucket - `recursive` (optional): Whether to access subfolders within the bucket (default: false) #### update_s3_source Update an existing S3 source connector. Parameters: - `source_id`: ID of the source connector to update - `remote_url` (optional): Updated S3 URI to the bucket or folder - `key` (optional): Updated AWS access key ID - `secret` (optional): Updated AWS secret access key - `token` (optional): Updated AWS STS session token - `anonymous` (optional): Whether to use anonymous authentication - `endpoint_url` (optional): Updated custom URL - `recursive` (optional): Updated subfolder access setting #### delete_s3_source Delete an S3 source connector. Parameters: - `source_id`: ID of the source connector to delete ### Destinations #### list_destinations Lists available destinations from the Unstructured API. Parameters: - `destination_type` (optional): Filter destinations by connector type #### get_destination_info Get detailed information about a specific destination connector. Parameters: - `destination_id`: ID of the destination connector to get information for #### create_s3_destination Create an S3 destination connector. Parameters: - `name`: Unique name for the connector - `remote_url`: S3 URI to the bucket or folder (e.g., s3://my-bucket/) - `key`: AWS access key ID - `secret`: AWS secret access key - `token` (optional): AWS STS session token for temporary access - `endpoint_url` (optional): Custom URL if connecting to a non-AWS S3 bucket #### update_s3_destination Update an existing S3 destination connector. Parameters: - `destination_id`: ID of the destination connector to update - `remote_url` (optional): Updated S3 URI to the bucket or folder - `key` (optional): Updated AWS access key ID - `secret` (optional): Updated AWS secret access key - `token` (optional): Updated AWS STS session token - `endpoint_url` (optional): Updated custom URL #### delete_s3_destination Delete an S3 destination connector. Parameters: - `destination_id`: ID of the destination connector to delete ### Workflows #### list_workflows Lists workflows from the Unstructured API. Parameters: - `destination_id` (optional): Filter by destination connector ID - `source_id` (optional): Filter by source connector ID - `status` (optional): Filter by workflow status #### get_workflow_info Get detailed information about a specific workflow. Parameters: - `workflow_id`: ID of the workflow to get information for #### create_workflow Create a new workflow. Parameters: - `workflow_config`: Dictionary containing the workflow configuration (must include required fields as per CreateWorkflow model) #### run_workflow Run a specific workflow. Parameters: - `workflow_id`: ID of the workflow to run #### update_workflow Update an existing workflow. Parameters: - `workflow_id`: ID of the workflow to update - `workflow_config`: Dictionary containing the updated workflow configuration (must include required fields as per UpdateWorkflow model) #### delete_workflow Delete a specific workflow. Parameters: - `workflow_id`: ID of the workflow to delete ## Claude Desktop Integration To install in Claude Desktop: 1. Go to `~/Library/Application Support/Claude/` and create a `claude_desktop_config.json`. 2. In that file add: ```bash { "mcpServers": { "UNS_MCP": { "command": "ABSOLUTE/PATH/TO/.local/bin/uv", "args": [ "--directory", "ABSOLUTE/PATH/TO/UNS-MCP", "run", "server.py" ], "disabled": false } } } ``` 3. Restart Claude Desktop. 4. Example Issues seen from Claude Desktop. - You will see `No destinations found` when you query for a list of destionation connectors. Check your API key in `.env`, it needs to be your personal key in `https://platform.unstructured.io/app/account/api-keys`. ## Debugging tools Anthropic provides `MCP Inspector` tool to debug/test your MCP server. Run the following command to spin up a debugging UI. From there, you will be able to add environment variables (pointing to your local env) on the left pane. Include your personal API key there as env var. Go to `tools`, you can test out the capabilities you add to the MCP server. ``` mcp dev server.py ``` ## Running locally minimal client ``` uv run python minimal_client/run.py server.py ```