Deep Research with MCP
by @wanghan0501
Multi-source deep research agent using MCP search tools (minimax web_search or zai-mcp-server web_search_prime).
clawhub install deep-research-with-mcpπ About This Skill
name: Deep Research with MCP slug: deep-research-with-mcp version: 1.1.1 description: Multi-source deep research agent using MCP search tools (minimax web_search or zai-mcp-server web_search_prime). homepage: https://github.com/wanghan0501/deep-research-with-mcp metadata: emoji: "π¬" category: "research" requires: bins: ["mcporter", "curl", "python3"] license: MIT-0 mcp_requirements: search_tools: - name: "MiniMax.web_search" description: "Primary MCP search tool (recommended)" required: true - name: "web-search-prime.web_search_prime" description: "Alternative MCP search tool" required: true
Deep Research with MCP π¬
A powerful, self-contained deep research skill that produces thorough, cited reports from multiple web sources. Uses MCP-configured search tools (minimax web_search or zai-mcp-server web_search_prime).
Prerequisites
Before using this skill, ensure you have configured at least one MCP search tool:
1. MiniMax web_search (recommended)
- Configure via minimax MCP server with web_search tool
2. web-search-prime web_search_prime
- Configure via web-search-prime MCP server with web_search_prime tool
If neither MCP is configured, the skill will not work.
How It Works
When the user asks for research on any topic, follow this workflow:
Step 0: Check MCP Search Availability
First verify MCP search tool availability:
# Check available MCP servers via mcporter
mcporter list
Priority:
1. MiniMax.web_search
mcporter call MiniMax.web_search query:"keyword"
2. web-search-prime.web_search_prime
mcporter call web-search-prime.web_search_prime search_query:"keyword"
Step 1: Understand the Goal (30 seconds)
Ask 1-2 quick clarifying questions:
If the user says "just research it" β skip ahead with reasonable defaults.
Step 2: Plan the Research (think before searching)
Break the topic into 3-5 research sub-questions. For example:
Step 3: Execute Multi-Source Search
Use MCP search tools to query:
# Using zai-mcp-server web_search_prime
mcporter call web-search-prime.web_search_prime search_query:""Using minimax web_search
mcporter call MiniMax.web_search query:""
Search strategy:
Step 4: Deep-Read Key Sources
For the most promising URLs, fetch full content:
curl -sL "" | python3 -c "
import sys, re
html = sys.stdin.read()
Strip tags, get text
text = re.sub('<[^>]+>', ' ', html)
text = re.sub(r'\s+', ' ', text).strip()
print(text[:5000])
"
Read 3-5 key sources in full for depth. Don't just rely on search snippets.
Step 5: Synthesize & Write Report
Structure the report as:
# [Topic]: Deep Research Report
*Generated: [date] | Sources: [N] | Confidence: [High/Medium/Low]*Executive Summary
[3-5 sentence overview of key findings]1. [First Major Theme]
[Findings with inline citations]
Key point (Source Name)
Supporting data (Source Name) 2. [Second Major Theme]
...3. [Third Major Theme]
...Key Takeaways
[Actionable insight 1]
[Actionable insight 2]
[Actionable insight 3] Sources
1. Title β [one-line summary]
2. ...Methodology
Searched [N] queries across web and news. Analyzed [M] sources.
Sub-questions investigated: [list]
Step 6: Save & Deliver
Save report to the current agent's working directory (auto-resolves to actual runtime path):
mkdir -p research/[slug]
Write report to research/[slug]/report.md
Then deliver:
Quality Rules
1. Every claim needs a source. No unsourced assertions. 2. Cross-reference. If only one source says it, flag it as unverified. 3. Recency matters. Prefer sources from the last 12 months. 4. Acknowledge gaps. If you couldn't find good info on a sub-question, say so. 5. No hallucination. If you don't know, say "insufficient data found."
Examples
"Research the current state of nuclear fusion energy"
"Deep dive into Rust vs Go for backend services in 2026"
"Research the best strategies for bootstrapping a SaaS business"
"What's happening with the US housing market right now?"
For Sub-Agent Usage
When spawning as a sub-agent, include the full research request and context:
sessions_spawn(
task: "Run deep research on [TOPIC]. Follow the deep-research-with-mcp SKILL.md workflow.
Goal: [user's goal]
Specific angles: [any specifics]
Save report to research/[slug]/report.md (relative to agent's working directory)
When done, wake the main session with key findings.",
label: "research-[slug]",
model: "opus"
)
Requirements
web_search tool (recommended)
- zai-mcp-server with web_search_prime tool
π‘ Examples
"Research the current state of nuclear fusion energy"
"Deep dive into Rust vs Go for backend services in 2026"
"Research the best strategies for bootstrapping a SaaS business"
"What's happening with the US housing market right now?"
βοΈ Configuration
Before using this skill, ensure you have configured at least one MCP search tool:
1. MiniMax web_search (recommended)
- Configure via minimax MCP server with web_search tool
2. web-search-prime web_search_prime
- Configure via web-search-prime MCP server with web_search_prime tool
If neither MCP is configured, the skill will not work.