SourceSync.ai▌
by scmdr
Streamline knowledge with SourceSync.ai's document management software for seamless archiving, search, and retrieval acr
Integrates with SourceSync.ai's knowledge management platform to enable semantic search, document management, and content ingestion from diverse sources for AI-driven knowledge retrieval and document analysis.
Both formats append explainx.ai attribution and the canonical URL for this MCP server listing.
best for
- / Knowledge workers building searchable document repositories
- / Teams needing AI-powered content retrieval and analysis
- / Researchers organizing and querying large document collections
capabilities
- / Ingest content from text, URLs, websites, and external services
- / Perform semantic and hybrid searches across knowledge bases
- / Manage and organize documents in namespaces
- / Retrieve and update stored documents
- / Connect to external data sources
- / Parse and access content from URLs
what it does
Connects to SourceSync.ai's knowledge management platform to ingest, search, and manage documents from various sources using AI-driven semantic search.
about
SourceSync.ai is an official MCP server published by scmdr that provides AI assistants with tools and capabilities via the Model Context Protocol. Streamline knowledge with SourceSync.ai's document management software for seamless archiving, search, and retrieval acr It is categorized under productivity.
how to install
You can install SourceSync.ai in your AI client of choice. Use the install panel on this page to get one-click setup for Cursor, Claude Desktop, VS Code, and other MCP-compatible clients. This server runs locally on your machine via the stdio transport.
license
MIT
SourceSync.ai is released under the MIT license. This is a permissive open-source license, meaning you can freely use, modify, and distribute the software.
readme
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 ./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": "[email protected]"
}
}
},
"tenantId": "tenant_XXX"
}
}
{
"name": "ingest_dropbox",
"arguments": {
"namespaceId": "your_namespace_id",
"ingestConfig": {
"source": "DROPBOX",
"config": {
"connectionId": "connection_XXX",
"metadata": {
"source": "dropbox",
"account": "[email protected]"
}
}
},
"tenantId": "tenant_XXX"
}
}
{
"name": "ingest_onedrive",
"arguments": {
"namespaceId": "your_namespace_id",
"ingestConfig": {
"source": "ONEDRIVE",
"config": {
"connectionId": "connection_XXX",
"metadata": {
"source": "onedrive",
"account": "[email protected]"
}
}
},
"tenantId": "tenant_XXX"
}
}
{
"name": "ingest_box",
"arguments": {
"namespaceId": "your_namespace_id",
"ingestConfig": {
"source": "BOX",
"config": {
"connectionId": "connection_XXX",
"metadata": {
"source": "box",
"owner": "[email protected]"
}
}
},
"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",
"tena
---
FAQ
- What is the SourceSync.ai MCP server?
- SourceSync.ai is a Model Context Protocol (MCP) server profile on explainx.ai. MCP lets AI hosts (e.g. Claude Desktop, Cursor) call tools and resources through a standard interface; this page summarizes categories, install hints, and community ratings.
- How do MCP servers relate to agent skills?
- Skills are reusable instruction packages (often SKILL.md); MCP servers expose live capabilities. Teams frequently combine both—skills for workflows, MCP for APIs and data. See explainx.ai/skills and explainx.ai/mcp-servers for parallel directories.
- How are reviews shown for SourceSync.ai?
- This profile displays 74 aggregated ratings (sample rows for discoverability plus signed-in user reviews). Average score is about 4.8 out of 5—verify behavior in your own environment before production use.
Use Cases▌
Extended AI Capabilities
Add new capabilities to Claude beyond text generation
Example
Access external data sources, execute code, interact with tools and services
Transform Claude from chatbot to action-taking agent
Context Enhancement
Provide Claude with access to relevant context and data
Example
Load project documentation, access knowledge bases, query databases
Get more accurate, context-aware responses
Workflow Automation
Automate multi-step workflows combining AI and external tools
Example
Research → Summarize → Create document → Send notification
Complete complex tasks end-to-end without manual steps
Implementation Guide▌
Prerequisites
- ›Claude Desktop 0.7.0+ or Cursor IDE with MCP support
- ›Basic understanding of MCP architecture and capabilities
- ›Access credentials for integrated services (if required)
- ›Willingness to experiment and iterate on configuration
Time Estimate
15-60 minutes depending on server complexity
Installation Steps
- 1.Install MCP server: npm install -g [package-name] or via GitHub
- 2.Add server configuration to ~/.claude/mcp.json
- 3.Provide required credentials and configuration
- 4.Restart Claude Desktop to load new server
- 5.Test basic functionality with simple prompts
- 6.Explore capabilities and experiment with use cases
- 7.Document successful patterns for reuse
Troubleshooting
- ⚠MCP server not loading: Check config syntax, verify installation
- ⚠Connection errors: Check network, firewall, credentials
- ⚠Feature not working: Read server docs, check required parameters
- ⚠Performance issues: Monitor resource usage, check for network latency
- ⚠Conflicts with other servers: Check port assignments, namespace collisions
Best Practices▌
✓ Do
- +Read server documentation thoroughly before setup
- +Start with simple use cases to validate functionality
- +Test in non-production environment first
- +Monitor resource usage and performance
- +Keep servers updated for bug fixes and new features
- +Document configuration for team members
- +Use environment variables for sensitive configuration
✗ Don't
- −Don't grant overly permissive access to MCP servers
- −Don't skip reading security considerations in docs
- −Don't expose sensitive data without proper controls
- −Don't run untrusted MCP servers without code review
- −Don't ignore error messages—investigate root cause
💡 Pro Tips
- ★Combine multiple MCP servers for powerful workflows
- ★Create custom MCP servers for your specific needs
- ★Share successful configurations with team
- ★Use MCP inspector for debugging
- ★Join MCP community for tips and troubleshooting
Technical Details▌
Architecture
Model Context Protocol standardizes how AI hosts (Claude, Cursor) communicate with external tools and data sources through server implementations.
Protocols
- Model Context Protocol (MCP)
- JSON-RPC 2.0
- stdio or HTTP transport
Compatibility
- Claude Desktop
- Cursor IDE
- Custom MCP clients
When to Use This▌
✓ Use When
Use when you need Claude to access external data, execute actions, or integrate with tools. Best for extending AI capabilities beyond conversation.
✗ Avoid When
Avoid when native integrations exist (use official APIs directly), for real-time critical systems, or when security/compliance requires zero external dependencies.
Integration▌
- →Tool composition: Chain multiple MCP tools in workflows
- →Context augmentation: Provide AI with relevant external data
- →Action delegation: Let AI execute tasks on external systems
- →Bidirectional sync: Keep AI context and external systems in sync
Discussion
Product Hunt–style comments (not star reviews)- No comments yet — start the thread.
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Ratings
4.8★★★★★74 reviews- ★★★★★Chaitanya Patil· Dec 28, 2024
We wired SourceSync.ai into a staging workspace; the listing’s GitHub and npm pointers saved time versus hunting across READMEs.
- ★★★★★Mateo Yang· Dec 28, 2024
SourceSync.ai is a well-scoped MCP server in the explainx.ai directory — install snippets and categories matched our Claude Code setup.
- ★★★★★Isabella Thomas· Dec 28, 2024
We wired SourceSync.ai into a staging workspace; the listing’s GitHub and npm pointers saved time versus hunting across READMEs.
- ★★★★★Ren Martinez· Dec 24, 2024
SourceSync.ai reduced integration guesswork — categories and install configs on the listing matched the upstream repo.
- ★★★★★Li Mensah· Dec 24, 2024
I recommend SourceSync.ai for teams standardizing on MCP; the explainx.ai page compares cleanly with sibling servers.
- ★★★★★Sakura Harris· Dec 24, 2024
According to our notes, SourceSync.ai benefits from clear Model Context Protocol framing — fewer ambiguous “AI plugin” claims.
- ★★★★★Kwame Taylor· Dec 24, 2024
SourceSync.ai is among the better-indexed MCP projects we tried; the explainx.ai summary tracks the official description.
- ★★★★★Piyush G· Nov 19, 2024
SourceSync.ai reduced integration guesswork — categories and install configs on the listing matched the upstream repo.
- ★★★★★Li Park· Nov 19, 2024
SourceSync.ai reduced integration guesswork — categories and install configs on the listing matched the upstream repo.
- ★★★★★Valentina Kim· Nov 15, 2024
We wired SourceSync.ai into a staging workspace; the listing’s GitHub and npm pointers saved time versus hunting across READMEs.
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