MCP Salesforce Lite

# mcp-salesforce-lite Simple and lightweight Salesforce MCP server for connecting AI assistants to Salesforce data. Ideal for prototyping and small projects. [](https://pypi.org/project/mcp-salesforce-lite/) [](https://pypi.org/project/mcp-salesforce-lite/) [](https://opensource.org/licenses/MIT) [](https://github.com/luvl/mcp-salesforce-lite/stargazers) **📦 Install from PyPI:** `pip install mcp-salesforce-lite` **🔗 PyPI Package:** https://pypi.org/project/mcp-salesforce-lite/ **📚 GitHub Repository:** https://github.com/luvl/mcp-salesforce-lite ## Demo See the MCP Salesforce Lite server in action with Claude Desktop:  *The demo shows Claude Desktop using the MCP server to interact with Salesforce data - querying objects, retrieving records, and performing CRUD operations seamlessly.* ## Overview This MCP (Model Context Protocol) server provides AI assistants like Claude with secure access to Salesforce data and operations. It implements the MCP standard to enable seamless integration between AI applications and Salesforce CRM. ## Features - 🔐 Secure Salesforce authentication via OAuth 2.0 - 📊 Access to Salesforce objects (Accounts, Contacts, Opportunities, etc.) - 🔍 SOQL query execution - 📝 CRUD operations on Salesforce records - 🛡️ Built-in security and rate limiting - 🚀 Easy setup and configuration ## Quick Usage ```bash # Install the package pip install mcp-salesforce-lite # Use with Claude Desktop (recommended) uvx --from mcp-salesforce-lite mcp-salesforce-lite # Or run directly mcp-salesforce-lite ``` **Works with:** Claude Desktop, any MCP-compatible AI assistant ## Quick Start with Claude Desktop ### Production Usage (Recommended) The easiest way to use this MCP server is to install it directly from PyPI and configure it with Claude Desktop. #### Step 1: Configure Claude Desktop Add the following configuration to your Claude Desktop settings file: **Configuration File Location:** - **macOS/Linux:** `~/Library/Application Support/Claude/claude_desktop_config.json` - **Windows:** `%APPDATA%\Claude\claude_desktop_config.json` **Configuration:** ```json { "mcpServers": { "salesforce-lite": { "command": "uvx", "args": [ "--from", "mcp-salesforce-lite", "mcp-salesforce-lite" ], "env": { "SALESFORCE_ACCESS_TOKEN": "your_access_token", "SALESFORCE_INSTANCE_URL": "your_instance_url" } } } } ``` #### Step 2: Set Up Salesforce Credentials Replace the environment variables in the configuration: - `SALESFORCE_ACCESS_TOKEN`: Your Salesforce access token - `SALESFORCE_INSTANCE_URL`: Your Salesforce instance URL (e.g., `https://yourcompany.my.salesforce.com`) #### Step 3: Restart Claude Desktop After saving the configuration, restart Claude Desktop. You should see a hammer icon indicating that tools are available. #### Step 4: Test the Integration Try asking Claude: - "List available Salesforce objects" - "Describe the Account object" - "Execute a SOQL query to get recent leads" ## Prerequisites - Python 3.10 or higher - Salesforce Developer/Production org - Connected App configured in Salesforce ## Development Setup If you want to modify or contribute to this MCP server, follow these development setup instructions. ### Installation #### Option 1: Using uv (Recommended for development) ```bash # Install uv if you haven't already brew install uv # macOS # or curl -LsSf https://astral.sh/uv/install.sh | sh # Linux/macOS # Clone and install the server git clone https://github.com/luvl/mcp-salesforce-lite.git cd mcp-salesforce-lite uv sync ``` #### Option 2: Using Poetry ```bash git clone https://github.com/luvl/mcp-salesforce-lite.git cd mcp-salesforce-lite poetry install ``` ### Salesforce Development Setup Create a `.env` file in the project root: ```env SALESFORCE_ACCESS_TOKEN=your_access_token SALESFORCE_INSTANCE_URL=your_instance_url ``` ## Usage ### Development Mode First, make sure you have your Salesforce credentials configured in your `.env` file. #### Method 1: Direct Python Execution ```bash # Run the server directly python src/mcp_salesforce_lite/server.py ``` #### Method 2: Using Poetry ```bash # Run with Poetry poetry run python src/mcp_salesforce_lite/server.py ``` #### Method 3: Using UV (Recommended) ```bash # Run with UV uv run python src/mcp_salesforce_lite/server.py ``` ### Testing with MCP Inspector If you have the MCP CLI installed, you can test your server: ```bash # Test with MCP Inspector mcp inspector # Or run in development mode mcp dev src/mcp_salesforce_lite/server.py ``` ### How to Release the Server as a Pip Package The server can be packaged and distributed via PyPI using the included `pyproject.toml` configuration. ## Available Tools The server provides the following tools that AI assistants can use: ### Query Tools - `soql_query`: Execute SOQL queries (schema must be defined to carefully ask for confirmation of UPDATE and DELETE operations) - `search_records`: Search records across multiple objects with limit and pagination - `get_record`: Retrieve a specific record by ID with limit and pagination ### CRUD Operations - `create_record`: Create new records (make sure to describe_object first, and find the reference fields of the objects) - `update_record`: Update existing records - `delete_record`: Delete records ### Metadata Tools - `describe_object_definition`: Get object metadata and field information with pagination - `list_avail_objects`: List available Salesforce objects with limit and pagination ## Development Claude Desktop Integration If you're developing or running the server from source, you can use these alternative configurations: **💡 Tip:** Example configuration files are provided in the `examples/` directory: - `examples/claude_config_direct.json` - Direct Python execution - `examples/claude_config_poetry.json` - Poetry execution - `examples/claude_config_uv.json` - UV execution (recommended) ### Option 1: Direct Python Execution ```json { "mcpServers": { "salesforce-lite": { "command": "python", "args": ["/ABSOLUTE/PATH/TO/mcp-salesforce-lite/src/mcp_salesforce_lite/server.py"], "env": { "SALESFORCE_ACCESS_TOKEN": "your_access_token", "SALESFORCE_INSTANCE_URL": "your_instance_url" } } } } ``` ### Option 2: Poetry Execution ```json { "mcpServers": { "salesforce-lite": { "command": "poetry", "args": [ "--directory", "/ABSOLUTE/PATH/TO/mcp-salesforce-lite", "run", "python", "src/mcp_salesforce_lite/server.py" ], "env": { "SALESFORCE_ACCESS_TOKEN": "your_access_token", "SALESFORCE_INSTANCE_URL": "your_instance_url" } } } } ``` ### Option 3: UV Execution (Recommended for Development) ```json { "mcpServers": { "salesforce-lite": { "command": "uv", "args": [ "--directory", "/ABSOLUTE/PATH/TO/mcp-salesforce-lite", "run", "python", "src/mcp_salesforce_lite/server.py" ], "env": { "SALESFORCE_ACCESS_TOKEN": "your_access_token", "SALESFORCE_INSTANCE_URL": "your_instance_url" } } } } ``` ## Project Structure ``` mcp-salesforce-lite/ ├── src/ │ └── mcp_salesforce_lite/ │ ├── __init__.py │ ├── server.py # Main MCP server │ ├── client.py # Salesforce client wrapper │ ├── config.py # Configuration management │ └── tools/ │ ├── __init__.py │ ├── query.py # SOQL query tools │ ├── crud.py # Create, Read, Update, Delete tools │ └── metadata.py # Object metadata tools ├── examples/ │ ├── basic_usage.py │ └── claude_config.json ├── assets/ │ └── sf-demo.gif # Demo GIF showing usage ├── .env.example ├── pyproject.toml ├── poetry.lock └── uv.lock ``` ## Release ### Prerequisites 1. **Register for PyPI Production**: Go to https://pypi.org/account/register/ 2. **Enable 2FA**: Set up two-factor authentication in your account settings 3. **Create API Token**: Go to https://pypi.org/manage/account/token/ and create a token 4. **Update .pypirc**: Replace `pypi-YOUR_PRODUCTION_TOKEN_FROM_PYPI_ORG_HERE` with your actual token ### Publishing Process 1. **Test on TestPyPI first**: ```bash # Build the package uv build # or: poetry build # Upload to TestPyPI twine upload --repository testpypi --config-file .pypirc dist/* # Test install from TestPyPI pip install --index-url https://test.pypi.org/simple/ --extra-index-url https://pypi.org/simple/ mcp-salesforce-lite ``` 2. **Publish to Production PyPI**: ```bash # Upload to production PyPI twine upload --repository pypi --config-file .pypirc dist/* # Test install from production PyPI pip install mcp-salesforce-lite ``` ### Version Management To publish a new version: 1. Update the version in `pyproject.toml` 2. Rebuild: `uv build` or `poetry build` 3. Upload: `twine upload --repository pypi --config-file .pypirc dist/*`