developer-tools

UniFuncs

by unifuncs

UniFuncs offers a TypeScript bridge to the google web search api, enabling web search and reading with Express and NPX.

Provides a bridge to the UniFuncs API for web search and web reading capabilities through TypeScript implementation with Express and NPX commands.

github stars

8

Deep research with up to 50 iterationsAsync task processing for complex queriesMultiple output formats and reference styles

best for

  • / Researchers needing comprehensive web analysis
  • / Developers building search-powered applications
  • / Content creators gathering source material
  • / AI assistants requiring web data access

capabilities

  • / Search the web with filtering and pagination
  • / Extract clean content from web pages
  • / Perform deep search with streaming results
  • / Create async research tasks with custom parameters
  • / Configure research depth and domain scope
  • / Export results in multiple formats

what it does

Connects MCP to UniFuncs API for web search, content extraction, and deep research capabilities. Offers both real-time and async processing for complex research tasks.

about

UniFuncs is an official MCP server published by unifuncs that provides AI assistants with tools and capabilities via the Model Context Protocol. UniFuncs offers a TypeScript bridge to the google web search api, enabling web search and reading with Express and NPX. It is categorized under developer tools.

how to install

You can install UniFuncs in your AI client of choice. Use the install panel on this page to get one-click setup for Cursor, Claude Desktop, VS Code, and other MCP-compatible clients. This server runs locally on your machine via the stdio transport.

license

MIT

UniFuncs is released under the MIT license. This is a permissive open-source license, meaning you can freely use, modify, and distribute the software.

readme

UniFuncs MCP Server

MCP Server for the UniFuncs API - Enhanced with Deep Search and Deep Research capabilities

Features

This MCP server provides access to the following UniFuncs APIs:

1. Web Search (web-search)

Real-time web search with comprehensive results

  • Search across the internet with keywords
  • Filter by freshness (Day/Week/Month/Year)
  • Pagination support (1-50 results per page)
  • Multiple output formats (JSON/Markdown/Text)

2. Web Reader (web-reader)

Extract detailed content from web pages

  • Clean content extraction
  • Optional image inclusion
  • Link summary support
  • Markdown output

3. Deep Search - Sync (deep-search-sync)

Real-time deep search with immediate results

  • Model: S3
  • Streaming support
  • Instant response

4. Deep Search - Async (deep-search-create-task + deep-search-query-task)

Asynchronous deep search for complex queries

  • Create task and get task_id immediately
  • Poll for task status and results
  • Background processing for large queries

5. Deep Research (deep-research-create-task + deep-research-query-task)

Comprehensive deep research capabilities

  • Models: U1, U1-Pro
  • Customizable research parameters:
    • Introduction: Set researcher persona
    • Reference style: link/number/footnote
    • Max depth: Up to 50 iterations (25 recommended)
    • Domain scope: Limit search to specific domains
    • Domain blacklist: Exclude specific domains
    • Custom output prompts
    • Important URLs, keywords, and prompts
  • Async task management

Setup

API Key

Get a UniFuncs API Key: https://unifuncs.com/account

NPX (STDIO)

{
    "mcpServers": {
        "unifuncs": {
            "command": "npx",
            "args": [
                "-y",
                "@unifuncs/ufn-mcp-server"
            ],
            "env": {
                "UNIFUNCS_API_KEY": "sk-**********"
            }
        }
    }
}

SSE Server

For SSE transport, set the environment variable:

export UNIFUNCS_SSE_SERVER=true
export UNIFUNCS_SSE_SERVER_PORT=5656  # Optional, default is 5656

Or use the --sse flag:

npx @unifuncs/ufn-mcp-server --sse

Tool Reference

web-search

Query: Search keywords
Freshness: Day | Week | Month | Year (optional)
Page: Page number, default 1 (optional)
Count: Results per page, 1-50, default 10 (optional)
Format: json | markdown | text, default json (optional)

web-reader

URL: Page URL to read
Format: markdown (optional)
IncludeImages: boolean (optional)
LinkSummary: boolean (optional)

deep-search-sync

Model: s3 (default: s3)
Messages: Array of {role: "user"|"assistant"|"system", content: string}
Stream: boolean (default: false)

deep-search-create-task

Model: s3 (default: s3)
Messages: Array of {role: "user"|"assistant"|"system", content: string}
Returns: task_id for querying status

deep-search-query-task

Task_ID: Task ID from create_task
Returns: Task status, progress, and results when completed

deep-research-create-task

Model: u1 | u1-pro (default: u1)
Content: Research question/topic
Introduction: Researcher persona (optional)
Reference_Style: link | number | footnote (default: link)
Generate_Summary: boolean (default: false)
Max_Depth: 1-50 (default: 25, recommended)
Domain_Scope: Comma-separated domains (optional)
Domain_Blacklist: Comma-separated domains to exclude (optional)
Output_Prompt: Custom output template (optional)
Important_URLs: Comma-separated URLs (optional)
Important_Keywords: Comma-separated keywords (optional)
Important_Prompt: Important prompt content (optional)
Push_To_Share: boolean (default: false)
Set_Public: boolean (default: false)
Returns: task_id for querying status

deep-research-query-task

Task_ID: Task ID from create_task
Returns: Task status, progress, and results when completed

Examples

Web Search

{
  "query": "OpenClaw AI",
  "count": 5,
  "format": "json"
}

Deep Search Async

// Create task
{
  "model": "s3",
  "messages": [
    { "role": "user", "content": "What are the latest developments in AI?" }
  ]
}

// Query task (use returned task_id)
{
  "task_id": "3aff2a91-7795-4b73-8dab-0593551a27a1"
}

Deep Research

// Create research task
{
  "model": "u1",
  "content": "Analyze the impact of AI on healthcare",
  "max_depth": 25,
  "domain_scope": "arxiv.org, nature.com",
  "generate_summary": true
}

// Query research task
{
  "task_id": "research-task-id-here"
}

Pricing

  • Web Search: Pay per request
  • Web Reader: Pay per request
  • Deep Search: Pay per token usage
  • Deep Research:
    • U1: 0.6 PTC/M Tokens
    • U1-Pro: 1.2 PTC/M Tokens

For detailed pricing, visit: https://unifuncs.com/pricing

Support

License

MIT

Changelog

v0.1.0 (2026-02-25)

  • Added Deep Search sync API support
  • Added Deep Search async API (create_task + query_task)
  • Added Deep Research async API (create_task + query_task)
  • Enhanced documentation with all tool references
  • Improved error handling

v0.0.6

  • Initial release with web-search and web-reader

FAQ

What is the UniFuncs MCP server?
UniFuncs is a Model Context Protocol (MCP) server profile on explainx.ai. MCP lets AI hosts (e.g. Claude Desktop, Cursor) call tools and resources through a standard interface; this page summarizes categories, install hints, and community ratings.
How do MCP servers relate to agent skills?
Skills are reusable instruction packages (often SKILL.md); MCP servers expose live capabilities. Teams frequently combine both—skills for workflows, MCP for APIs and data. See explainx.ai/skills and explainx.ai/mcp-servers for parallel directories.
How are reviews shown for UniFuncs?
This profile displays 10 aggregated ratings (sample rows for discoverability plus signed-in user reviews). Average score is about 4.5 out of 5—verify behavior in your own environment before production use.
MCP server reviews

Ratings

4.510 reviews
  • Shikha Mishra· Oct 10, 2024

    UniFuncs is among the better-indexed MCP projects we tried; the explainx.ai summary tracks the official description.

  • Piyush G· Sep 9, 2024

    We evaluated UniFuncs against two servers with overlapping tools; this profile had the clearer scope statement.

  • Chaitanya Patil· Aug 8, 2024

    Useful MCP listing: UniFuncs is the kind of server we cite when onboarding engineers to host + tool permissions.

  • Sakshi Patil· Jul 7, 2024

    UniFuncs reduced integration guesswork — categories and install configs on the listing matched the upstream repo.

  • Ganesh Mohane· Jun 6, 2024

    I recommend UniFuncs for teams standardizing on MCP; the explainx.ai page compares cleanly with sibling servers.

  • Oshnikdeep· May 5, 2024

    Strong directory entry: UniFuncs surfaces stars and publisher context so we could sanity-check maintenance before adopting.

  • Dhruvi Jain· Apr 4, 2024

    UniFuncs has been reliable for tool-calling workflows; the MCP profile page is a good permalink for internal docs.

  • Rahul Santra· Mar 3, 2024

    According to our notes, UniFuncs benefits from clear Model Context Protocol framing — fewer ambiguous “AI plugin” claims.

  • Pratham Ware· Feb 2, 2024

    We wired UniFuncs into a staging workspace; the listing’s GitHub and npm pointers saved time versus hunting across READMEs.

  • Yash Thakker· Jan 1, 2024

    UniFuncs is a well-scoped MCP server in the explainx.ai directory — install snippets and categories matched our Claude Code setup.