What is scmdr sourcesyncai mcp
SourceSync.ai MCP Server
*
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:
- Open Cursor Settings
- Go to
Features > MCP Servers
- Click
+ Add New MCP Server
- Enter the following:
- Name:
sourcesyncai-mcp
(or your preferred name) - Type:
command
- Command:
env SOURCESYNCAI_API_KEY=your-api-key npx -y sourcesyncai-mcp
- Name:
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:
-
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
- macOS:
-
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"
}
}
}
}
- 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 operationsSOURCESYNC_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 namespacelist_namespaces
: List all namespacesget_namespace
: Get details of a specific namespaceupdate_namespace
: Update a namespacedelete_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 contentingest_urls
: Ingest content from URLsingest_sitemap
: Ingest content from a sitemapingest_website
: Ingest content from a websiteingest_notion
: Ingest content from Notioningest_google_drive
: Ingest content from Google Driveingest_dropbox
: Ingest content from Dropboxingest_onedrive
: Ingest content from OneDriveingest_box
: Ingest content from Boxget_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 filtersupdateDocuments
: Update document metadatadeleteDocuments
: Delete documentsresyncDocuments
: Resync documentsfetchUrlContent
: 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 searchhybrid_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 servicelist_connections
: List all connectionsget_connection
: Get details of a specific connectionupdate_connection
: Update a connectionrevoke_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:
-
Verify Paths: Ensure all paths in your configuration are absolute paths, not relative.
-
Check Permissions: Ensure the server file has execution permissions (
chmod +x dist/index.js
). -
Enable Developer Mode: In Claude Desktop, enable Developer Mode and check the MCP Log File.
-
Test the Server: Run the server directly from the command line:
node /path/to/sourcesyncai-mcp/dist/index.js
-
Restart AI Client: After making changes, completely restart Claude Desktop or Cursor.
-
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 setupsrc/schemas.ts
: Schema definitions for all toolssrc/sourcesync.ts
: Client for interacting with SourceSync.ai APIsrc/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:
- First, use
getDocuments
withincludeConfig.parsedTextFileUrl: true
to get documents with their content URLs - Extract the URL from the document response
- Use
fetchUrlContent
to retrieve the actual content:
{
"name": "fetchUrlContent",
"arguments": {
"url": "https://example.com"
}
}
Leave a Comment
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.
Related MCP Servers
chrisdoc hevy mcp
sylphlab pdf reader mcp
An MCP server built with Node.js/TypeScript that allows AI agents to securely read PDF files (local or URL) and extract text, metadata, or page counts. Uses pdf-parse.
aashari mcp server atlassian bitbucket
Node.js/TypeScript MCP server for Atlassian Bitbucket. Enables AI systems (LLMs) to interact with workspaces, repositories, and pull requests via tools (list, get, comment, search). Connects AI directly to version control workflows through the standard MCP interface.
aashari mcp server atlassian confluence
Node.js/TypeScript MCP server for Atlassian Confluence. Provides tools enabling AI systems (LLMs) to list/get spaces & pages (content formatted as Markdown) and search via CQL. Connects AI seamlessly to Confluence knowledge bases using the standard MCP interface.
prisma prisma
Next-generation ORM for Node.js & TypeScript | PostgreSQL, MySQL, MariaDB, SQL Server, SQLite, MongoDB and CockroachDB
Zzzccs123 mcp sentry
mcp sentry for typescript sdk
zhuzhoulin dify mcp server
zhongmingyuan mcp my mac
zhixiaoqiang desktop image manager mcp
MCP 服务器,用于管理桌面图片、查看详情、压缩、移动等(完全让Trae实现)
zhixiaoqiang antd components mcp
An MCP service for Ant Design components query | 一个减少 Ant Design 组件代码生成幻觉的 MCP 服务,包含系统提示词、组件文档、API 文档、代码示例和更新日志查询
Submit Your MCP Server
Share your MCP server with the community
Submit Now