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mcp-server

by seonokkim
OverviewSchemaSourceRelated ServersDiscussionsAdmin
Python
Local

Server Configuration

Describes the environment variables required to run the server.

NameRequiredDescriptionDefault

No arguments

Instructions

Guidance the server publishes about itself, which clients place ahead of the tool catalog so the model reads it before choosing anything.

This server publishes no instructions, or was last inspected before Glama recorded them.

Capabilities

Features and capabilities supported by this server

Protocol revision2025-11-25

CapabilityDetails
tools
{
  "listChanged": false
}
prompts
{
  "listChanged": false
}
resources
{
  "subscribe": false,
  "listChanged": false
}
experimental
{}

Tools

Functions exposed to the LLM to take actions

NameDescription
get_docsA

Search the latest docs for a given query and library. Supports langchain, openai, and llama-index.

Args: query: The query to search for (e.g. "Chroma DB") library: The library to search in (e.g. "langchain")

Returns: Text from the docs

setup_chroma_dbA
Set up a ChromaDB vector database with LangChain integration.

Args:
    texts: List of text strings to be embedded and stored in the vector database.
    metadatas: Optional list of metadata dictionaries corresponding to each text.
    persist_directory: Optional directory path to persist the vector database.
                      If None, an in-memory database will be created.

Returns:
    Dict containing retriever info and success status.
query_chroma_dbA
Query a ChromaDB vector database using LangChain integration.

Args:
    query: The query string to search for in the vector database.
    persist_directory: Directory path where the vector database is persisted.
    top_k: Number of top results to return (default: 3).

Returns:
    List of retrieved documents with their content and metadata.
chroma_db_demoB
Demonstrate the ChromaDB vector database with LangChain integration.

Args:
    sample_texts: Optional list of sample texts to use for demonstration.
                 If not provided, default sample texts will be used.

Returns:
    Results of setting up and querying the ChromaDB vector database.

Prompts

Interactive templates invoked by user choice

NameDescription

No prompts

Resources

Contextual data attached and managed by the client

NameDescription

No resources

Deploy Server
One endpoint for every MCP toolRayrun runs every MCP server behind one URL and holds the credentials. Each call is decided per client, tool, and argument, then recorded.ray.runAd

TDQS

A3.9/5.0

Scored across 4 tools

Disambiguation5/5

Each tool has a clearly distinct purpose: get_docs searches documentation, setup_chroma_db initializes a vector database, query_chroma_db retrieves results, and chroma_db_demo runs a combined demonstration. No two tools overlap in a way that would cause misselection.

Naming Consistency4/5

Three tools follow a clear verb_noun pattern (get_docs, setup_chroma_db, query_chroma_db), while chroma_db_demo deviates to a noun_noun style. However, all names use snake_case and are predictable and readable.

Tool Count5/5

With four tools focused on docs search and ChromaDB operations, the count is well-scoped and each tool earns its place. It is neither too thin nor overloaded for the apparent purpose.

Completeness4/5

The core workflows are covered: search docs, set up a vector DB, and query it. Minor gaps exist—no update/delete for vectors and docs search limited to three libraries—but agents can work around these limitations.

Maintenance

ActivityInactive
ResponsivenessNo issues

Resources