AgentIndex icon
AgentIndex
nepa-mcp logo
nepa-mcp
★ 18
vs
deep-research logo
deep-research
★ 4.7k

nepa-mcp vs deep-research

nepa-mcp: NEPA MCP is a Model Context Protocol (MCP) server layer designed to provide AI agents with structured access to extensive federal environmental, regulatory, biological, cultural, socioeconomic, and jurisdictional data. It supports NEPA screening and permitting research by integrating data from numerous federal agencies and offering capabilities like interactive map composition.; deep-research: Deep Research is an AI-powered tool designed to generate comprehensive research reports rapidly, leveraging advanced AI models and internet connectivity. It prioritizes user privacy by processing and storing all data locally.

01

TL;DR

nepa-mcp logo
nepa-mcpRAG / Knowledge Base · ★ 18

Assisting AI agents in NEPA screening and permitting research workflows.

Read nepa-mcp full review →
deep-research logo
deep-researchRAG / Knowledge Base · ★ 4.7k

Rapidly generate in-depth research reports for personal and professional use.

Read deep-research full review →
02

Side-by-Side Comparison

Field
nepa-mcp logonepa-mcp
deep-research logodeep-research
Category
RAG / Knowledge Base
RAG / Knowledge Base
Stars
★ 18
★ 4.7k
License
BSD-3-Clause
MIT
Install Command
pipx install nepa-mcp && pipx ensurepath
docker run -d --name deep-research -p 3333:3000 xiangfa/deep-research
Updated
4d ago
4mo ago
Open Source
Yes
Yes
Website
↗ Visit
↗ Visit
GitHub
↗ GitHub
↗ GitHub
Tags
AI Agents, Environmental Data, Regulatory Research
AI Research, LLM, Privacy-focused
03

Features

nepa-mcp logonepa-mcp
01Provides AI agents structured access to comprehensive federal environmental and regulatory data.
02Offers 85 environmental and regulatory research capabilities through 22 MCP servers, 53 tools, and 32 GIS layers.
03Includes an interactive Map Composer for generating maps or GeoJSON exports from 32 selectable GIS overlays.
04Supports integration with popular AI clients like Codex, Claude Code, and VS Code.
deep-research logodeep-research
01Rapidly generates comprehensive research reports in minutes.
02Ensures privacy by processing and storing all data locally in the browser.
03Supports a wide range of mainstream large language models (LLMs).
04Integrates with various web search engines for enhanced information gathering.
05Allows uploading and processing local files to build a knowledge base.
04

Use Cases

nepa-mcp logonepa-mcp
↳Assisting AI agents in NEPA screening and permitting research workflows.
↳Accessing and analyzing federal environmental, regulatory, and geospatial data for project planning.
↳Composing interactive maps or GeoJSON exports for geospatial workflows (e.g., QGIS, ArcGIS).
↳Performing environmental assessments and site screening based on various federal agency data.
deep-research logodeep-research
↳Rapidly generate in-depth research reports for personal and professional use.
↳Serve as a deep research as a service (SaaS) platform via SSE API.
↳Integrate deep research functionality into other AI applications using MCP.
FAQ

FAQ

What is the difference between nepa-mcp and deep-research?
Both nepa-mcp and deep-research are in the RAG / Knowledge Base category. nepa-mcp has 18 stars, while deep-research has 4.7k stars.
Which is better, nepa-mcp or deep-research?
The best choice depends on your use case. Choose nepa-mcp if Assisting AI agents in NEPA screening and permitting research workflows., and deep-research if Rapidly generate in-depth research reports for personal and professional use..
Is nepa-mcp free or open source?
Yes, nepa-mcp is open source on GitHub (BSD-3-Clause).
Is deep-research free or open source?
Yes, deep-research is open source on GitHub (MIT).
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