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Grist MCP Server: Seamless APIs & Scalable Workflows - MCP Implementation

Grist MCP Server: Seamless APIs & Scalable Workflows

Seamlessly integrate Grist APIs with MCP Server—built for developers, scalability, and smarter workflows. No hassle, just results.

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About Grist MCP Server

What is Grist MCP Server: Seamless APIs & Scalable Workflows?

Grist MCP Server is a specialized tool that bridges Grist spreadsheets with language models through a robust API interface. It simplifies integration by providing programmatic access to Grist data, enabling developers to automate workflows, analyze datasets, and build dynamic applications. This server acts as a versatile middleware, supporting everything from basic data retrieval to complex operations like filtering, sorting, and real-time updates—all while maintaining secure API authentication.

Key Features of Grist MCP Server: Seamless APIs & Scalable Workflows?

  • Data Accessibility: Directly query or modify records in Grist tables using language models, eliminating manual data entry.
  • Hierarchical Navigation: Traverse organizations, workspaces, documents, and tables systematically to manage data at scale.
  • Advanced Querying: Apply filters, sort records, and limit results with JSON-based parameters for precise data manipulation.
  • CRUD Capabilities: Create, read, update, and delete records seamlessly via standardized API endpoints.
  • Security First: Authentication via API keys ensures controlled access to sensitive data.

Grist MCP Server Features

How to Use Grist MCP Server: Seamless APIs & Scalable Workflows?

Deploying the server involves three core steps:

  1. Setup: Install via pip or Docker, then configure environment variables with your Grist API credentials.
  2. Integration: Use tools like list_organizations to explore data structures, then target specific tables/documents for CRUD operations.
  3. Execution: Trigger workflows programmatically—for example, auto-populate records based on model outputs or generate reports on-demand.

For development environments, the server can run locally or via Docker, with configurations tailored for platforms like Claude Desktop.

Use Cases of Grist MCP Server: Seamless APIs & Scalable Workflows?

  • Data Automation: Sync Grist tables with external systems by scripting bulk updates or deletions.
  • AI-Powered Analysis: Query Grist datasets directly through language models to generate summaries or recommendations.
  • Dynamic Reporting: Build dashboards that fetch real-time data from Grist for visualizations in tools like Tableau.
  • Workflow Orchestration: Integrate Grist with chatbots or automation platforms to trigger actions based on spreadsheet changes.

Grist MCP Server FAQ

FAQ from Grist MCP Server: Seamless APIs & Scalable Workflows?

Q: What are the system requirements?

A: Requires Python 3.8+, the listed Python packages, and a valid Grist API key. Docker support is optional but recommended for isolation.

Q: How do I secure API keys?

A: Store keys in environment variables using a .env file to avoid hardcoding credentials in source files.

Q: Can I customize query parameters?

A: Yes, use JSON filters and sort parameters to refine results. Refer to the Grist API docs for syntax details.

Q: What error handling is built-in?

A: The server returns status codes and messages for failed operations (e.g., invalid IDs), aiding in debugging workflows.

Q: How do I deploy in production?

A: Use Docker for consistent environments. Ensure your API keys are rotated periodically and access is restricted via Grist’s permission settings.

Content

Grist MCP Server

An MCP server implementation that provides tools for interacting with the Grist API, enabling integration between Grist spreadsheets and language models.

Features

  • Access Grist data directly from language models
  • List organizations, workspaces, documents, tables, and columns
  • Query, add, update, and delete records in Grist tables
  • Filter and sort data with rich query capabilities
  • Secure API key-based authentication

Tools

list_organizations

List all Grist organizations that the user has access to.

Returns: A list of organizations with their IDs, names, and domains.

list_workspaces

List all workspaces in a Grist organization.

Inputs:

  • org_id (int or string): The ID of the organization to list workspaces for

Returns: A list of workspaces with their IDs and names.

list_documents

List all documents in a Grist workspace.

Inputs:

  • workspace_id (int): The ID of the workspace to list documents for

Returns: A list of documents with their IDs and names.

list_tables

List all tables in a Grist document.

Inputs:

  • doc_id (string): The ID of the document to list tables for

Returns: A list of tables with their IDs.

list_columns

List all columns in a Grist table.

Inputs:

  • doc_id (string): The ID of the document containing the table
  • table_id (string): The ID of the table to list columns for

Returns: A list of columns with their IDs and field data.

list_records

List records in a Grist table with optional filtering, sorting, and limiting.

Inputs:

  • doc_id (string): The ID of the document containing the table
  • table_id (string): The ID of the table to list records from
  • filter_json (string, optional): JSON string for filtering records (e.g., '{"column_name": ["value1", "value2"]}')
  • sort (string, optional): Comma-separated list of columns to sort by (prefix with '-' for descending order)
  • limit (int, optional): Maximum number of records to return

Returns: A list of records with their IDs and field data.

add_grist_records

Add records to a Grist table.

Inputs:

  • doc_id (string): The ID of the document containing the table
  • table_id (string): The ID of the table to add records to
  • records (array): List of records to add as dictionaries of field values

Returns: A list of IDs for the newly created records.

update_grist_records

Update records in a Grist table.

Inputs:

  • doc_id (string): The ID of the document containing the table
  • table_id (string): The ID of the table to update records in
  • records (array): List of records to update (each must include "id" and field values)

Returns: A list of IDs for the updated records.

delete_grist_records

Delete records from a Grist table.

Inputs:

  • doc_id (string): The ID of the document containing the table
  • table_id (string): The ID of the table to delete records from
  • record_ids (array): List of record IDs to delete

Returns: A dictionary containing the operation status and a message.

Usage

The Grist MCP Server is designed for:

  • Analyzing and summarizing Grist data
  • Creating, updating, and deleting records programmatically
  • Building reports and visualizations based on Grist data
  • Answering questions about data stored in Grist tables
  • Connecting Grist with language models for natural language queries

Requirements

  • Python 3.8+
  • A valid Grist API key
  • The following Python packages: fastmcp, httpx, pydantic, python-dotenv

Setup

Environment Variables

Create a .env file with the following:

GRIST_API_KEY=your_api_key_here
GRIST_API_HOST=https://docs.getgrist.com/api

Replace your_api_key_here with your actual Grist API key, which you can find in your Grist account settings.

Configuration

Usage with Claude Desktop

Add this to your claude_desktop_config.json:

Direct Python

{
  "mcpServers": {
    "grist-mcp": {
      "command": "python",
      "args": [
        "-m", "grist_mcp_server"
      ]
    }
  }
}

Docker

{
  "mcpServers": {
    "grist-mcp": {
      "command": "docker",
      "args": [
        "run",
        "--rm",
        "-i",
        "-e", "GRIST_API_KEY=your_api_key_here",
        "-e", "GRIST_API_HOST=https://docs.getgrist.com/api",
        "mcp/grist-mcp-server"
      ]
    }
  }
}

Building

Docker:

docker build -t mcp/grist-mcp-server .

Installation

pip install mcp-server-grist

Or manually:

git clone https://github.com/yourusername/mcp-server-grist.git
cd mcp-server-grist
pip install -r requirements.txt

License

This MCP server is licensed under the MIT License.

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