scmdr sourcesyncai mcp

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What is scmdr sourcesyncai mcp

SourceSync.ai MCP Server

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A Model Context Protocol (MCP) server implementation for the SourceSync.ai API. This server allows AI models to interact with SourceSync.ai's knowledge management platform through a standardized interface.

Features

  • Manage namespaces for organizing knowledge
  • Ingest content from various sources (text, URLs, websites, external services)
  • Retrieve, update, and manage documents stored in your knowledge base
  • Perform semantic and hybrid searches against your knowledge base
  • Access document content directly from parsed text URLs
  • Manage connections to external services
  • Default configuration support for seamless AI integration

Installation

Running with npx

# Install and run with your API key and tenant ID
env SOURCESYNC_API_KEY=your_api_key npx -y sourcesyncai-mcp

Installing via Smithery

To install sourcesyncai-mcp for Claude Desktop automatically via Smithery:

npx -y @smithery/cli install @pbteja1998/sourcesyncai-mcp --client claude

Manual Installation

# Clone the repository
git clone https://github.com/yourusername/sourcesyncai-mcp.git
cd sourcesyncai-mcp

# Install dependencies
npm install

# Build the project
npm run build

# Run the server
node dist/index.js

Running on Cursor

To configure SourceSync.ai MCP in Cursor:

  1. Open Cursor Settings
  2. Go to Features > MCP Servers
  3. Click + Add New MCP Server
  4. Enter the following:
    • Name: sourcesyncai-mcp (or your preferred name)
    • Type: command
    • Command: env SOURCESYNCAI_API_KEY=your-api-key npx -y sourcesyncai-mcp

After adding, you can use SourceSync.ai tools with Cursor's AI features by describing your knowledge management needs.

Running on Windsurf

Add this to your ./claude-codeium/windsurf/model_config.json:

{
  "mcpServers": {
    "sourcesyncai-mcp": {
      "command": "npx",
      "args": ["-y", "soucesyncai-mcp"],
      "env": {
        "SOURCESYNC_API_KEY": "your_api_key",
        "SOURCESYNC_NAMESPACE_ID": "your_namespace_id",
        "SOURCESYNC_TENANT_ID": "your_tenant_id"
      }
    }
  }
}

Running on Claude Desktop

To use this MCP server with Claude Desktop:

  1. Locate the Claude Desktop configuration file:

    • macOS: ~/Library/Application Support/Claude/claude_desktop_config.json
    • Windows: %APPDATA%\Claude\claude_desktop_config.json
    • Linux: ~/.config/Claude/claude_desktop_config.json
  2. Edit the configuration file to add the SourceSync.ai MCP server:

{
  "mcpServers": {
    "sourcesyncai-mcp": {
      "command": "npx",
      "args": ["-y", "sourcesyncai-mcp"],
      "env": {
        "SOURCESYNC_API_KEY": "your_api_key",
        "SOURCESYNC_NAMESPACE_ID": "your_namespace_id",
        "SOURCESYNC_TENANT_ID": "your_tenant_id"
      }
    }
  }
}
  1. Save the configuration file and restart Claude Desktop

Configuration

Environment Variables

Required

  • SOURCESYNC_API_KEY: Your SourceSync.ai API key (required)

Optional

  • SOURCESYNC_NAMESPACE_ID: Default namespace ID to use for operations
  • SOURCESYNC_TENANT_ID: Your tenant ID (optional)

Configuration Examples

Basic configuration with default values:

export SOURCESYNC_API_KEY=your_api_key
export SOURCESYNC_TENANT_ID=your_tenant_id
export SOURCESYNC_NAMESPACE_ID=your_namespace_id

Available Tools

Authentication

  • validate_api_key: Validate a SourceSync.ai API key
{
  "name": "validate_api_key",
  "arguments": {}
}

Namespaces

  • create_namespace: Create a new namespace
  • list_namespaces: List all namespaces
  • get_namespace: Get details of a specific namespace
  • update_namespace: Update a namespace
  • delete_namespace: Delete a namespace
{
  "name": "create_namespace",
  "arguments": {
    "name": "my-namespace",
    "fileStorageConfig": {
      "provider": "S3_COMPATIBLE",
      "config": {
        "endpoint": "s3.amazonaws.com",
        "accessKey": "your_access_key",
        "secretKey": "your_secret_key",
        "bucket": "your_bucket",
        "region": "us-east-1"
      }
    },
    "vectorStorageConfig": {
      "provider": "PINECONE",
      "config": {
        "apiKey": "your_pinecone_api_key",
        "environment": "your_environment",
        "index": "your_index"
      }
    },
    "embeddingModelConfig": {
      "provider": "OPENAI",
      "config": {
        "apiKey": "your_openai_api_key",
        "model": "text-embedding-3-small"
      }
    },
    "tenantId": "tenant_XXX"
  }
}
{
  "name": "list_namespaces",
  "arguments": {
    "tenantId": "tenant_XXX"
  }
}
{
  "name": "get_namespace",
  "arguments": {
    "namespaceId": "namespace_XXX",
    "tenantId": "tenant_XXX"
  }
}
{
  "name": "update_namespace",
  "arguments": {
    "namespaceId": "namespace_XXX",
    "tenantId": "tenant_XXX",
    "name": "updated-namespace-name"
  }
}
{
  "name": "delete_namespace",
  "arguments": {
    "namespaceId": "namespace_XXX",
    "tenantId": "tenant_XXX"
  }
}

Data Ingestion

  • ingest_text: Ingest text content
  • ingest_urls: Ingest content from URLs
  • ingest_sitemap: Ingest content from a sitemap
  • ingest_website: Ingest content from a website
  • ingest_notion: Ingest content from Notion
  • ingest_google_drive: Ingest content from Google Drive
  • ingest_dropbox: Ingest content from Dropbox
  • ingest_onedrive: Ingest content from OneDrive
  • ingest_box: Ingest content from Box
  • get_ingest_job_run_status: Get the status of an ingestion job run
{
  "name": "ingest_text",
  "arguments": {
    "namespaceId": "your_namespace_id",
    "ingestConfig": {
      "source": "TEXT",
      "config": {
        "name": "example-document",
        "text": "This is an example document for ingestion.",
        "metadata": {
          "category": "example",
          "author": "AI Assistant"
        }
      }
    },
    "tenantId": "tenant_XXX"
  }
}
{
  "name": "ingest_urls",
  "arguments": {
    "namespaceId": "your_namespace_id",
    "ingestConfig": {
      "source": "URLS",
      "config": {
        "urls": ["https://example.com/page1", "https://example.com/page2"],
        "metadata": {
          "source": "web",
          "category": "documentation"
        }
      }
    },
    "tenantId": "tenant_XXX"
  }
}
{
  "name": "ingest_sitemap",
  "arguments": {
    "namespaceId": "your_namespace_id",
    "ingestConfig": {
      "source": "SITEMAP",
      "config": {
        "url": "https://example.com/sitemap.xml",
        "metadata": {
          "source": "sitemap",
          "website": "example.com"
        }
      }
    },
    "tenantId": "tenant_XXX"
  }
}
{
  "name": "ingest_website",
  "arguments": {
    "namespaceId": "your_namespace_id",
    "ingestConfig": {
      "source": "WEBSITE",
      "config": {
        "url": "https://example.com",
        "maxDepth": 3,
        "maxPages": 100,
        "metadata": {
          "source": "website",
          "domain": "example.com"
        }
      }
    },
    "tenantId": "tenant_XXX"
  }
}
{
  "name": "ingest_notion",
  "arguments": {
    "namespaceId": "your_namespace_id",
    "ingestConfig": {
      "source": "NOTION",
      "config": {
        "connectionId": "your_notion_connection_id",
        "metadata": {
          "source": "notion",
          "workspace": "My Workspace"
        }
      }
    },
    "tenantId": "your_tenant_id"
  }
}
{
  "name": "ingest_google_drive",
  "arguments": {
    "namespaceId": "your_namespace_id",
    "ingestConfig": {
      "source": "GOOGLE_DRIVE",
      "config": {
        "connectionId": "connection_XXX",
        "metadata": {
          "source": "google_drive",
          "owner": "user@example.com"
        }
      }
    },
    "tenantId": "tenant_XXX"
  }
}
{
  "name": "ingest_dropbox",
  "arguments": {
    "namespaceId": "your_namespace_id",
    "ingestConfig": {
      "source": "DROPBOX",
      "config": {
        "connectionId": "connection_XXX",
        "metadata": {
          "source": "dropbox",
          "account": "user@example.com"
        }
      }
    },
    "tenantId": "tenant_XXX"
  }
}
{
  "name": "ingest_onedrive",
  "arguments": {
    "namespaceId": "your_namespace_id",
    "ingestConfig": {
      "source": "ONEDRIVE",
      "config": {
        "connectionId": "connection_XXX",
        "metadata": {
          "source": "onedrive",
          "account": "user@example.com"
        }
      }
    },
    "tenantId": "tenant_XXX"
  }
}
{
  "name": "ingest_box",
  "arguments": {
    "namespaceId": "your_namespace_id",
    "ingestConfig": {
      "source": "BOX",
      "config": {
        "connectionId": "connection_XXX",
        "metadata": {
          "source": "box",
          "owner": "user@example.com"
        }
      }
    },
    "tenantId": "tenant_XXX"
  }
}
{
  "name": "get_ingest_job_run_status",
  "arguments": {
    "namespaceId": "your_namespace_id",
    "ingestJobRunId": "ingest_job_run_XXX",
    "tenantId": "tenant_XXX"
  }
}

Documents

  • getDocuments: Retrieve documents with optional filters
  • updateDocuments: Update document metadata
  • deleteDocuments: Delete documents
  • resyncDocuments: Resync documents
  • fetchUrlContent: Fetch text content from document URLs
{
  "name": "getDocuments",
  "arguments": {
    "namespaceId": "namespace_XXX",
    "tenantId": "tenant_XXX",
    "filterConfig": {
      "documentTypes": ["PDF"]
    },
    "includeConfig": {
      "parsedTextFileUrl": true
    }
  }
}
{
  "name": "updateDocuments",
  "arguments": {
    "namespaceId": "namespace_XXX",
    "tenantId": "tenant_XXX",
    "documentIds": ["doc_XXX", "doc_YYY"],
    "filterConfig": {
      "documentIds": ["doc_XXX", "doc_YYY"]
    },
    "data": {
      "metadata": {
        "status": "reviewed",
        "category": "technical"
      }
    }
  }
}
{
  "name": "deleteDocuments",
  "arguments": {
    "namespaceId": "namespace_XXX",
    "tenantId": "tenant_XXX",
    "documentIds": ["doc_XXX", "doc_YYY"],
    "filterConfig": {
      "documentIds": ["doc_XXX", "doc_YYY"]
    }
  }
}
{
  "name": "resyncDocuments",
  "arguments": {
    "namespaceId": "namespace_XXX",
    "tenantId": "tenant_XXX",
    "documentIds": ["doc_XXX", "doc_YYY"],
    "filterConfig": {
      "documentIds": ["doc_XXX", "doc_YYY"]
    }
  }
}
{
  "name": "fetchUrlContent",
  "arguments": {
    "url": "https://api.sourcesync.ai/v1/documents/doc_XXX/content?format=text",
    "apiKey": "your_api_key",
    "tenantId": "tenant_XXX"
  }
}

Search

  • semantic_search: Perform semantic search
  • hybrid_search: Perform hybrid search (semantic + keyword)
{
  "name": "semantic_search",
  "arguments": {
    "namespaceId": "your_namespace_id",
    "query": "example document",
    "topK": 5,
    "tenantId": "tenant_XXX"
  }
}
{
  "name": "hybrid_search",
  "arguments": {
    "namespaceId": "your_namespace_id",
    "query": "example document",
    "topK": 5,
    "tenantId": "tenant_XXX",
    "hybridConfig": {
      "semanticWeight": 0.7,
      "keywordWeight": 0.3
    }
  }
}

Connections

  • create_connection: Create a new connection to an external service
  • list_connections: List all connections
  • get_connection: Get details of a specific connection
  • update_connection: Update a connection
  • revoke_connection: Revoke a connection
{
  "name": "create_connection",
  "arguments": {
    "tenantId": "tenant_XXX",
    "namespaceId": "namespace_XXX",
    "name": "My Connection",
    "connector": "GOOGLE_DRIVE",
    "clientRedirectUrl": "https://your-app.com/callback"
  }
}
{
  "name": "list_connections",
  "arguments": {
    "tenantId": "tenant_XXX",
    "namespaceId": "namespace_XXX"
  }
}
{
  "name": "get_connection",
  "arguments": {
    "tenantId": "tenant_XXX",
    "namespaceId": "namespace_XXX",
    "connectionId": "connection_XXX"
  }
}
{
  "name": "update_connection",
  "arguments": {
    "tenantId": "tenant_XXX",
    "namespaceId": "namespace_XXX",
    "connectionId": "connection_XXX",
    "name": "Updated Connection Name",
    "clientRedirectUrl": "https://your-app.com/updated-callback"
  }
}
{
  "name": "revoke_connection",
  "arguments": {
    "tenantId": "tenant_XXX",
    "namespaceId": "namespace_XXX",
    "connectionId": "connection_XXX"
  }
}

Example Prompts

Here are some example prompts you can use with Claude or Cursor after configuring the MCP server:

  • "Search my SourceSync knowledge base for information about machine learning."
  • "Ingest this article into my SourceSync knowledge base: [URL]"
  • "Create a new namespace in SourceSync for my project documentation."
  • "List all the documents in my SourceSync namespace."
  • "Get the text content of document [document_id] from my SourceSync namespace."

Troubleshooting

Connection Issues

If you encounter issues connecting the SourceSync.ai MCP server:

  1. Verify Paths: Ensure all paths in your configuration are absolute paths, not relative.

  2. Check Permissions: Ensure the server file has execution permissions (chmod +x dist/index.js).

  3. Enable Developer Mode: In Claude Desktop, enable Developer Mode and check the MCP Log File.

  4. Test the Server: Run the server directly from the command line:

    node /path/to/sourcesyncai-mcp/dist/index.js
    
  5. Restart AI Client: After making changes, completely restart Claude Desktop or Cursor.

  6. Check Environment Variables: Ensure all required environment variables are correctly set.

Debug Logging

For detailed logging, add the DEBUG environment variable:

Development

Project Structure

  • src/index.ts: Main entry point and server setup
  • src/schemas.ts: Schema definitions for all tools
  • src/sourcesync.ts: Client for interacting with SourceSync.ai API
  • src/sourcesync.types.ts: TypeScript type definitions

Building and Testing

# Build the project
npm run build

# Run tests
npm test

License

MIT

Links

  • SourceSync.ai Documentation
  • SourceSync.ai API Reference
  • Model Context Protocol

Document content retrieval workflow:

  1. First, use getDocuments with includeConfig.parsedTextFileUrl: true to get documents with their content URLs
  2. Extract the URL from the document response
  3. Use fetchUrlContent to retrieve the actual content:
{
  "name": "fetchUrlContent",
  "arguments": {
    "url": "https://example.com"
  }
}

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Frequently Asked Questions

What is MCP?

MCP (Model Context Protocol) is an open protocol that standardizes how applications provide context to LLMs. Think of MCP like a USB-C port for AI applications, providing a standardized way to connect AI models to different data sources and tools.

What are MCP Servers?

MCP Servers are lightweight programs that expose specific capabilities through the standardized Model Context Protocol. They act as bridges between LLMs like Claude and various data sources or services, allowing secure access to files, databases, APIs, and other resources.

How do MCP Servers work?

MCP Servers follow a client-server architecture where a host application (like Claude Desktop) connects to multiple servers. Each server provides specific functionality through standardized endpoints and protocols, enabling Claude to access data and perform actions through the standardized protocol.

Are MCP Servers secure?

Yes, MCP Servers are designed with security in mind. They run locally with explicit configuration and permissions, require user approval for actions, and include built-in security features to prevent unauthorized access and ensure data privacy.

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