技能潮 SkillTide 提交收录
官方说明7 个来源MCP 服务8 天前
elhamid/llm-council

elhamid/llm-council

🐍 🏠 - Multi-LLM deliberation with anonymized peer review: parallel responses, anonymous ranking and…
在 GitHub 查看 ↗直链 · 无中转页
官方说明🐍 🏠 - Multi-LLM deliberation with anonymized peer review: parallel responses, anonymous ranking and synthesis, based on Andrej Karpathy's LLM Council concept.
配置模板(请按你的客户端调整)
claude mcp add llm-council -- npx -y llm-council
这是根据仓库名生成的可粘贴骨架,命令行参数与包名请以该项目 README 为准。
★ 数取值
8 ★ · elhamid/llm-council · 取自该仓库的 GitHub 页面 · (2026-10-16 20:00:20 核对)
来源明细
收录自 punkpeye/awesome-mcp-servers 榜单(我们从中收集的条目之一) · 条目类型:MCP 服务
收录与活跃
收录于 2026-10-09 · 最近见到 2026-10-16 · 共见到 32 次 · 被 7 个来源列出
评分构成
综合分 703 · 8 ★ · 7 个来源 · mcp
常见问题(答案都来自我们的记录)
怎么安装?
我们【没有】从该仓库取到安装命令(我们的 install 覆盖率只有约 4%)。请看它的 README 或 releases 页。
它适合谁 / 用来做什么?
我们把它归在这些标签下: MCP 服务。标签来自条目自身,不是我们强加的分类。
谁维护它、还在更新吗?
仓库 elhamid/llm-council;我们收录于 2026-10-09;最近见到 2026-10-16。这里没有"官方认证"或"质量评级"——我们只记录来源与时间。
第三方质量标记

LLM Council

以下摘录自该仓库的 README(片段) · 在 GitHub 读完整 README →

Fork notes (elhamid)
This is a fork of karpathy/llm-council.
Update — 2025-12-19 (Stability + auditability pass)
New in this fork since the previously published state:
- **Conversation history is complete again:** storage loads older runs from backend/data/conversations.json and supports the legacy data/ layout (including data/conversations/ per-conversation JSON files when present), so older runs show up in the UI.
- **Sidebar no longer truncates early:** the frontend now requests /api/conversations?limit=500 so the conversation list reliably shows full history.
- **Stage 2 judge duplication fixed:** Stage 2 now dedupes judge models so evaluation does not silently double-count the same judge.
- **Titles persist correctly:** after Stage 3 completes, a title is derived and saved to the conversation record, so it sticks across refreshes and appears in history.
- **Tooling + reproducibility:** added Stage 2 smoke/quality scripts and supporting evaluation artifacts to make regressions repeatable.
- **Roles updated + clarified:** earlier fork notes described roles as **Analyst / Researcher / Critic / Provocateur**; the implemented role set is now **Builder / Reviewer / Synthesizer / Contrarian** (with a provider-default mapping in backend/roles.py). This keeps the “multi-perspective” intent, but with clearer, more actionable role behavior.
Value added — 2025-12-14 (decision-quality focused)
- **Decision-auditable runs:** every council response is saved with a compact decision trace (Stage 1 answers, Stage 2 rankings, and the Stage 2→model mapping), so you can inspect *why* the Chairman concluded what it did — not just the final text.
- **Reduced “model-brand” bias in judging:** Stage 2 rankings operate on anonymized responses (Response A/B/C/…), and the label→model mapping is preserved for post-hoc review. This keeps peer review focused on content quality rather than model identity.
- **Role-separated council behavior:** explicit role specs (Analyst / Researcher / Critic / Provocateur + Chairman) make the council behave more like a real review board: one pushes rigor, one hunts missing facts, one stress-tests, one challenges assumptions — then the Chairman synthesizes.
- **Repeatable scoring across runs:** aggregated ranks (average rank + count) are persisted so you can compare council behavior over time and across prompts, instead of treating each run as a one-off chat.
Implementation notes (supporting the above)
- Real SSE endpoint (text/event-stream) for /api/conversations/{id}/message/stream with incremental stage*_start/complete events.
- Persist meta/metadata (label_to_model, aggregate_rankings, model_roles) so Stage2 renders correctly and the run is reviewable later.
- Frontend Stage2 reads msg.meta || msg.metadata so fork/upstream payload shapes both render.
----
The idea of this repo is that instead of asking a question to your favorite LLM provider (e.g. OpenAI GPT 5.1, Google Gemini 3.0 Pro, Anthropic Claude Sonnet 4.5, xAI Grok 4, eg.c), you can group them into your "LLM Council". This repo is a simple, local web app that essentially looks like ChatGPT except it uses OpenRouter to send your query to multiple LLMs, it then asks them to review and rank each other's work, and finally a Chairman LLM produces the final response.
来源
awesome · https://github.com/elhamid/llm-council
按领域浏览
MCP 服务
Traction
8 ★
收录于
昨天

更多MCP 服务

查看MCP 服务全部 5,525 条 →

所属领域与标签

每个标签都能点进去看同类的全部条目。数字是当前库里的真实条数。

浏览全部领域 →

← 返回索引