exa-mcp-server and web-research-assistant

These are competitors: Exa offers a commercial search API with native MCP integration for web search and crawling, while SearXNG provides a self-hosted, open-source metasearch alternative wrapped in MCP, targeting users with different infrastructure preferences and cost models.

exa-mcp-server
89
Verified
web-research-assistant
50
Established
Maintenance 25/25
Adoption 20/25
Maturity 25/25
Community 19/25
Maintenance 10/25
Adoption 8/25
Maturity 18/25
Community 14/25
Stars: 3,985
Forks: 302
Downloads: 64,323
Commits (30d): 53
Language: TypeScript
License: MIT
Stars: 6
Forks: 3
Downloads: 66
Commits (30d): 0
Language: Python
License: MIT
No risk flags
No risk flags

About exa-mcp-server

exa-labs/exa-mcp-server

Exa MCP for web search and web crawling!

Implements an MCP (Model Context Protocol) server that exposes Exa's search APIs—including specialized code search and company research—via HTTP transport to integrate with AI assistants and code editors (Cursor, VS Code, Claude Desktop, etc.). Offers both basic tools (web search, code context, page crawling) and advanced filtering capabilities, with optional Claude Skills for domain-specific workflows like competitor analysis. Deploys as a hosted endpoint or npm package, requiring only an API key for authentication.

About web-research-assistant

elad12390/web-research-assistant

MCP server for SearXNG with 13 production-ready tools for web search, package info, GitHub integration, error translation, API docs, and more

Implements the Model Context Protocol over stdio for seamless Claude Desktop and OpenCode integration, with configurable backends including local SearXNG, Exa AI neural search, crawl4ai for content extraction, and Pixabay for images. Exposes 4 MCP resources for direct data lookups (packages, repos, service status, changelogs) and 5 reusable prompt templates alongside the 13 tools, enabling AI agents to conduct structured research workflows with automatic response size limits and usage tracking.

Scores updated daily from GitHub, PyPI, and npm data. How scores work