How do I use kiro-research-mcp?

1. Click on "Install Server". 2. Wait a few minutes for the server to deploy. Once ready, it will show a "Started" state. 3. In the chat, type @ followed by the MCP server name and your instructions, e.g., "@kiro-research-mcp Research the impact of AI on healthcare in 2025" That's it! The server will respond to your query, and you can continue using it as needed. Here is a step-by-step guide with screenshots.

kiro-research-mcp

by thejusdutt

Overview Schema Related Servers Score Discussions

JavaScript

Remote

Kiro Research MCP Server

npm version License: MIT

A Claude Research-style MCP server implementing Anthropic's multi-agent research methodology that outperforms single-agent by 90.2%.

Features

🔍 Iterative Search - Start broad, then narrow (Claude Research methodology)
📊 Source Quality Scoring - Prioritizes primary sources over SEO content farms
📝 Citation Tracking - Automatic numbered citations [1], [2], etc.
📈 Scaling Rules - Built-in guidance for simple, comparison, and complex research
📋 Quality-Tiered Reports - Sources grouped by authority level

Related MCP server: MCP Hub

Quick Start

Installation

Use directly with npx (no installation required):

npx @thejusdutt/kiro-research-mcp

Or install globally:

npm install -g @thejusdutt/kiro-research-mcp

Configuration

Kiro IDE

Add to .kiro/settings/mcp.json:

{
  "mcpServers": {
    "research": {
      "command": "npx",
      "args": ["-y", "@thejusdutt/kiro-research-mcp"],
      "env": {
        "TAVILY_API_KEY": "your-tavily-api-key"
      },
      "autoApprove": ["web_search", "add_source", "get_citations", "research_session", "generate_report"]
    }
  }
}

Claude Desktop

Add to claude_desktop_config.json:

{
  "mcpServers": {
    "research": {
      "command": "npx",
      "args": ["-y", "@thejusdutt/kiro-research-mcp"],
      "env": {
        "TAVILY_API_KEY": "your-tavily-api-key"
      }
    }
  }
}

Get a Tavily API Key

Go to tavily.com
Sign up for free (1,000 searches/month free)
Copy your API key

Claude Research Methodology

This server implements the research methodology described in Anthropic's engineering blog:

Architecture

┌─────────────────────────────────────────────────────────────┐
│                    LEAD RESEARCHER (You)                     │
│  Plans strategy → Coordinates searches → Synthesizes         │
└─────────────────────────────────────────────────────────────┘
                              │
        ┌─────────────────────┼─────────────────────┐
        ▼                     ▼                     ▼
┌───────────────┐   ┌───────────────┐   ┌───────────────┐
│   SUBAGENT 1  │   │   SUBAGENT 2  │   │   SUBAGENT 3  │
│  (Aspect A)   │   │  (Aspect B)   │   │  (Aspect C)   │
└───────────────┘   └───────────────┘   └───────────────┘
        │                     │                     │
        └─────────────────────┼─────────────────────┘
                              ▼
                    ┌───────────────┐
                    │ CITATION AGENT│
                    │ Validates all │
                    │ claims/sources│
                    └───────────────┘

Scaling Rules

Task Type	Searches	Sources	Example
Simple fact	3-10	3-5	"What is WebAssembly?"
Comparison	10-15/aspect	4-6/aspect	"Compare React vs Vue"
Complex research	25+	10-15	"State of AI in healthcare 2025"

Source Quality Scoring

Anthropic found that agents often chose SEO content farms over authoritative sources. This server implements quality heuristics:

Score	Tier	Examples
10	Primary	Official docs, research papers, company blogs
9	Authoritative	.gov, .edu, major institutions
7	Quality	Quality journalism, expert analysis
5	General	General web content
3	Low	SEO farms, social media (deprioritized)

Search Strategy

Phase 1 - Broad Exploration: Start with 2-4 word queries
Phase 2 - Parallel Exploration: Search different aspects simultaneously
Phase 3 - Gap Filling: Target identified knowledge gaps
Phase 4 - Verification: Cross-reference key claims

Tools

`web_search`

Search the web with quality scoring.

Parameters:
- query: Search query (start broad, then refine)
- maxResults: Number of results (default: 10)
- sessionId: Session ID to track progress

`add_source`

Track a fetched URL as a citation source.

Parameters:
- sessionId: Research session ID
- url: URL of the source
- title: Title of the article
- author: (optional) Author name
- publishedDate: (optional) Publication date
- siteName: (optional) Site name

`research_session`

Manage research sessions with scaling guidance.

Actions:
- create: Start new session (provides scaling targets)
- update: Add findings and gaps
- status: Get progress metrics
- complete: Mark session done

`get_citations`

Get formatted citations.

Parameters:
- sessionId: Research session ID
- format: markdown, inline, apa, mla, chicago

`generate_report`

Generate a quality-tiered research report.

Parameters:
- sessionId: Research session ID
- title: (optional) Report title
- includeSources: Include sources section (default: true)
- includeGaps: Include gaps section (default: true)

Example Workflow

User: Research the current state of WebAssembly in 2025

1. Create session:
   research_session(action: "create", query: "WebAssembly 2025 state")
   → Returns scaling guidance: 10-15 searches, 5-8 sources

2. Broad search:
   web_search(query: "WebAssembly 2025", sessionId: "...")
   → Returns quality-scored results

3. Aspect searches:
   web_search(query: "WebAssembly server-side performance")
   web_search(query: "WebAssembly browser support 2025")
   web_search(query: "companies using WebAssembly production")

4. Fetch & track sources:
   mcp_fetch_fetch(url: "https://...")
   add_source(sessionId: "...", url: "...", title: "...")

5. Record findings:
   research_session(action: "update", findings: [...], gaps: [...])

6. Generate report:
   generate_report(sessionId: "...")
   → Quality-tiered report with citations

Environment Variables

Variable	Required	Description
`TAVILY_API_KEY`	Yes	Tavily API key for web search

Development

# Clone the repo
git clone https://github.com/thejusdutt/kiro-research-mcp.git
cd kiro-research-mcp

# Install dependencies
npm install

# Build
npm run build

# Run locally
node build/index.js

References

How we built our multi-agent research system - Anthropic Engineering
Model Context Protocol - MCP Documentation
Tavily API - Search API

License

This server cannot be installed

license - permissive license

quality - not tested

maintenance

How are these scores calculated?

Maintenance

–Maintainers

–Response time

–Release cycle

–Releases (12mo)

Commit activity

Resources

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