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SWEN.AI MCP Server (reference source)

Product site

This repository contains the reference implementation of the source code behind the public Model Context Protocol (MCP) server hosted at:

https://swen.ia.br/api/mcp

SWEN.AI is a Brazilian portal covering AI news, model benchmarks, tools and tutorials. This MCP server exposes that data to AI agents and MCP-compatible clients (Claude, Claude Code, etc.) with no API key required (IP-based rate limiting only).

This is not a runnable standalone package

The files here are copied verbatim from our private production monorepo so that developers can read, audit, and understand exactly what the hosted endpoint does. Authentication, rate-limiting, and infrastructure code are intentionally not included — see Security below.

To use the server, connect your MCP client directly to the hosted endpoint; there is nothing to install or run locally.

Connecting an MCP client

{
  "mcpServers": {
    "swen-ai": {
      "url": "https://swen.ia.br/api/mcp"
    }
  }
}

Related MCP server: claude-wilder-mcp

Available tools

Tool

Description

search_news

Search/list published AI news articles

get_news_article

Fetch a single news article by slug

list_ai_models

List tracked AI models

get_model

Fetch a single AI model by slug

get_intelligence_ranking

Get the canonical Artificial Analysis Intelligence Index ranking

search_tools

Search/list AI tools in the directory

list_tutorials

List tutorials

Every tool is a thin wrapper: it validates input, calls a fetchers.ts function to read from Postgres (via Supabase's REST API using the public anon key), maps the row to a stable public contract (mappers.ts / types.ts), and returns JSON.

Files in this repo

src/lib/api-v1/
  mcp-server.ts     tool registration (the 7 tools above)
  fetchers.ts       data-fetching functions (reads only, public anon key)
  mappers.ts        DB row → public contract mapping
  types.ts          public contract types (NewsItem, ModelItem, ...)
src/lib/ranking/
  fetch-aa.ts       canonical Artificial Analysis ranking logic (dedup + sort)
src/lib/benchmark/
  freshness.ts      filters out stale benchmark scores
src/lib/i18n/
  config.ts         locale constants used by the mappers

These are copied byte-for-byte from the production repo. They are kept in sync manually; they may lag the deployed version slightly.

Also see

Security

This repo deliberately excludes:

  • auth.ts — API key validation and rate-limiting logic

  • key-crypto.ts — API key hashing

  • Any environment variable, credential, or internal Supabase project reference beyond the two values that are public by design: NEXT_PUBLIC_SUPABASE_URL and NEXT_PUBLIC_SUPABASE_ANON_KEY (already shipped in every page's browser bundle on swen.ia.br; access is governed by Postgres Row Level Security, not by keeping this value secret).

If you believe you've found a security issue with the hosted endpoint, please report it privately rather than opening a public issue.

License

MIT — see LICENSE.

Available Tools

7 tools
get_intelligence_rankingGet AI Intelligence RankingB

The current AI model intelligence ranking (Artificial Analysis Intelligence Index), deduplicated by model family — one entry per model at its best configuration. Identical ordering to swen.ia.br/ranking and the SWEN.AI iOS app.

Inputs: limit.

get_modelGet AI ModelA

Get a single AI model by slug: pricing, context window, speed.

Inputs: slug (required).

get_news_articleGet AI News ArticleA

Get a single AI news article by slug.

Inputs: slug (required).

list_ai_modelsList AI ModelsA

List AI model catalog: pricing, context window, speed. From SWEN.AI benchmark database.

Inputs: limit, offset.

list_tutorialsList AI TutorialsC

Tutorials and guides directory. From SWEN.AI.

Inputs: limit, offset.

search_newsSearch AI NewsA

List recent AI news articles from SWEN.AI (Brazilian AI news portal). Returns summary + canonical link, never the full article body.

Inputs: limit, offset, category.

search_toolsSearch AI ToolsC

AI tools directory: pricing, ratings, categories. From SWEN.AI.

Inputs: limit, offset.

Tool Schema Changelog

Recent tool additions, removals, and schema changes observed during successful MCP inspections.

Loading tool schema changelog…

    TDQS

    A3.6/5.0

    Scored across 7 tools

    Disambiguation5/5

    Each tool targets a distinct resource: model, tool, tutorial, news, or ranking. The model-related tools (get_model, list_ai_models, get_intelligence_ranking) are clearly differentiated by purpose, and search_tools vs search_news are separated by the object being searched.

    Naming Consistency5/5

    All tool names follow a consistent verb_noun pattern using snake_case. The verbs (get, search, list) are applied predictably according to the action: get for single items, search for queries, and list for full catalogs or directories.

    Tool Count5/5

    With 7 tools, the server is well-scoped for its domain covering models, tools, tutorials, and news. Each tool serves a clear purpose without redundancy, fitting comfortably within the ideal 3-15 range.

    Completeness4/5

    The news and model sections are complete with list/search and get operations, but tutorials only have a list (no get tutorial by slug) and tools only have search (no get tool by ID). These are minor gaps that agents can work around using the existing search/list results.

    Maintenance

    ActivityMaintained
    ResponsivenessNo recent community issues

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