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MCP Knowledge Base Server
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6 months ago
First Indexed
3 months ago
Catalog Refreshed
Documentation & install
Readme and setup notes from the catalogue, plus a client-ready config you can copy for your MCP host.
Installation
Add the following to your MCP client configuration file.
Configuration
View docs{
"mcpServers": {
"dannwaneri-mcp-knowledge-base-server": {
"command": "node",
"args": [
"C:\\\\path\\\\to\\\\mcp-learning\\\\dist\\\\index.js"
]
}
}
}This MCP Knowledge Base Server exposes a structured knowledge base through multiple tools for fast semantic search and data retrieval, with a lightweight in-memory cache to speed repeated queries.
How to use
You connect an MCP client to this server to perform searches, browse categories, and retrieve entries by ID. Use the available tools to refine results, filter by category, and perform advanced searches with limits. Enable caching to accelerate repeated queries.
How to install
Prerequisites: Node.js and npm must be installed on your system.
Install dependencies and build the project.
npm install
npm run build
Configuration and usage notes
Configure your MCP client to load the knowledge base server as a local process. The server runs as a standard Node.js process that executes a built JavaScript file from the dist folder.
{
"mcpServers": {
"knowledge_base": {
"command": "node",
"args": ["C:\\path\\to\\mcp-learning\\dist\\index.js"]
}
}
}
Notes
The server exposes the following tools to interact with the knowledge base: search_knowledge, list_categories, get_by_category, get_by_id, advanced_search, and an in-memory caching mechanism with a 60-second TTL to speed repeated queries.
Available tools
search_knowledge
Search for relevant information using keywords to quickly locate knowledge base entries.
list_categories
List all available categories to help you navigate the knowledge base.
get_by_category
Filter entries by a specific category to narrow results.
get_by_id
Retrieve a specific entry by its unique ID.
advanced_search
Perform a refined search with category filters and result limits.
in_memory_cache
Cache results for 60 seconds to speed up repeated queries.