Add server: io.github.mateuslos/abstrator — recursive abstraction research MCP

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Valutazione

Difficoltà
2/5
Tempo stimato
1-3 ore
Idoneità per principianti
55/100
Tipo di issue
Funzionalità
Chiarezza
Abbastanza chiara
Stato di attività
Attiva
Stack tecnologico
docker, python
Ambito
release

Direzione di ricerca

Start by reading the registry's server submission requirements and checking how existing PyPI server submissions are represented; the issue provides a server.json proposal and ownership marker but names no registry files or tests. Confirm the submission meets the registry's validation requirements, then run the relevant validation or submission checks. Done means the registry accepts this server entry.

Scritto dal modello di indicizzazione a partire dal testo della issue.

Descrizione

Server submission

Package name: io.github.mateuslos/abstrator
PyPI: https://pypi.org/project/abstrator/0.1.0/
Repository: https://github.com/MateusLOS/abstrator
License: MIT

server.json
{
  "$schema": "https://static.modelcontextprotocol.io/schemas/2025-12-11/server.schema.json",
  "name": "io.github.mateuslos/abstrator",
  "title": "Abstrator",
  "description": "Recursive abstraction research — decomposes any topic into sub-concepts, researches each through 8 specialized lenses (meaning, theory, practice, best_practices, expert_views, advanced_methods, existing_tools, analogy), and synthesizes a professional-grade guide.",
  "version": "0.1.0",
  "packages": [
    {
      "registryType": "pypi",
      "identifier": "abstrator",
      "version": "0.1.0",
      "transport": {
        "type": "stdio",
        "command": "abstrator",
        "args": ["mcp"]
      }
    }
  ],
  "repository": {
    "url": "https://github.com/MateusLOS/abstrator"
  },
  "license": "MIT"
}
What it does

Abstrator is an MCP server + CLI that takes any question or topic and runs a recursive research chain:

  1. Decomposition — breaks the concept into simpler sub-concepts via LLM
  2. Lens-based research — each sub-concept is researched through 8 named lenses (meaning, theory, practice, best_practices, expert_views, advanced_methods, existing_tools, analogy) using local SearXNG + page fetching
  3. Bottom-up integration — synthesizes children findings into the parent, preserving conflicts and open questions
  4. Root synthesis — produces a professional-grade markdown guide with best practices, expert views, methodologies and tools
Primary tool: ask
ask(query: str, mode: "quick"|"standard"|"deep") -> str

Returns clean markdown ready to use in any AI conversation. No configuration needed with claude_code_cli provider (uses Claude Code OAuth).

Quick start
pip install abstrator
docker run -d -p 8888:8080 searxng/searxng
abstrator setup
claude mcp add abstrator -- abstrator mcp
Ownership verification

The <!-- mcp-name: io.github.mateuslos/abstrator --> marker is present in the README: https://github.com/MateusLOS/abstrator/blob/main/README.md

Lingua principale
Go
Stelle
7.4k
Fork
1k
Merge medio
17h 29m
PR unite (30g)
68

Preparare l'ambiente

Come iniziare

  1. Leggi tutta la issue e poi la guida ai contributi del progetto.
  2. Commenta sulla issue per dire che te ne occupi tu — evita che due persone facciano lo stesso lavoro.
  3. Fai un fork del repository e lavora su un branch.
  4. Apri una pull request che faccia riferimento al numero della issue.

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