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Glama
patanjali-22

mcpRAG

by patanjali-22
OverviewSchemaSourceRelated ServersDiscussionsAdmin
Local

Server Configuration

Describes the environment variables required to run the server.

NameRequiredDescriptionDefault
BRIGHTDATA_USERYesYour Bright Data account email/username.
BRIGHTDATA_PASSWORDYesYour Bright Data account password.

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
faq_retrieval_toolA

Retrieve the most relevant documents from FAQ collection. Use this tool when the user asks about F1 Racing.

Input:
    query: str -> The user query to retrieve the most relevant documents

Output:
    context: str -> most relevant documents retrieved from a vector DB
bright_data_web_search_toolA
Search for information on a given topic using Bright Data.
Use this tool when the user asks about a specific topic or question 
that is not related to general machine learning.

Input:
    query: str -> The user query to search for information

Output:
    context: list[str] -> list of most relevant web search results

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

A4.1/5.0

Scored across 2 tools

Disambiguation5/5

The two tools have clearly distinct purposes: one retrieves from a specific FAQ collection, the other performs general web searches. There is no functional overlap, and each tool's description directs usage to its intended context.

Naming Consistency5/5

Both tools use the same naming pattern: a descriptive source/domain prefix combined with the action and the suffix '_tool', all in snake_case. This is consistent and predictable.

Tool Count3/5

With only 2 tools, the server feels thin for a general RAG use case. The count is borderline—not excessive, but the minimal surface may leave agents wanting more specialized retrieval options.

Completeness2/5

The server only provides retrieval operations, with no tools for managing or updating the FAQ collection or ingesting new documents. This is a significant gap for a complete RAG workflow, potentially causing agent failures when asked to perform any write or update operation.

Maintenance

ActivityInactive
ResponsivenessNo issues

Resources