Skip to main content
Glama
sid12super

MCP-Deep-Researcher

by sid12super
OverviewSchemaSourceRelated ServersDiscussionsAdmin
Python
Local

Server Configuration

Describes the environment variables required to run the server.

NameRequiredDescriptionDefault
OPENAI_API_KEYYesOpenAI API key
TAVILY_API_KEYYesTavily API key

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
deep_researcher_researchA

Run a multi-agent research pipeline that decomposes a query into sub-questions, searches the web in parallel via Tavily, scores source credibility, and synthesizes a comprehensive markdown report with findings, knowledge gaps, and cited sources.

The pipeline has three stages:
  1. Planner — breaks the query into 3-5 targeted sub-questions (GPT-4o)
  2. Searcher — runs parallel Tavily web searches with credibility scoring
  3. Synthesizer — produces a structured markdown report (GPT-4o)

Results are cached for 24 hours. Identical (query + context + depth) combinations
return instantly on subsequent calls.

Args:
    params (ResearchInput): Validated input containing:
        - query (str): The research question (3-2000 chars)
        - search_depth (SearchDepth): 'basic' for speed or 'advanced' for depth
        - conversation_context (str): Prior research for multi-turn follow-ups

Returns:
    str: Markdown research report with executive summary, key findings per
         sub-question, knowledge gaps, and numbered source citations with
         credibility tags (high/medium/unverified).

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

A4.8/5.0

Scored across 1 tool

Disambiguation5/5

Only one tool exists, so there is zero ambiguity among tools. The tool's purpose is clearly defined.

Naming Consistency5/5

With a single tool, naming consistency is trivially perfect. The name 'deep_researcher_research' is descriptive and follows a clear pattern.

Tool Count5/5

The server is focused on a single, complex task (deep research). One tool is appropriate; adding more would likely complicate the interface unnecessarily.

Completeness5/5

The single tool covers the entire research pipeline—planning, searching, scoring, synthesizing—with caching. No obvious gaps within its stated purpose.

Maintenance

ActivityInactive
ResponsivenessNo issues

Resources