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Fable

作者:codeChap版本 0.1.0i★ –i–
注册名称io.github.codeChap/fable

安装

概览

作者提供的说明(英文原文)

Anthropic Claude Fable 5 MCP server — top-tier planning and code critique for handoff

PopNx MCP 的三大支柱

这三项永远不会合并成一个分数:意见、测量和人气是不同的东西。

它能帮你做什么

我们还没有为它写通俗的介绍。下面是我们从注册中心读取到的事实。

  • 连接方式: –
  • 传输方式:
  • 分类: 其他

安装

选择你使用的 AI 应用,然后复制设置。

安装之前

  • 基础检查:1 项中通过 1 项
  • 在你的电脑上运行,拥有你的用户账户的权限(文件、网络、应用)。
  • 注册中心没有列出需要填写的密钥。

作者没有在注册中心列出安装信息。请查看下方作者的 README。

它能做什么

它在你的电脑上运行;安装后,工具列表会显示在你的 AI 应用中。

基础检查i

我们检查的是任何人都能看到的信息;我们没有阅读代码。不适用的检查项不计入总数。 · 检查于 2026年11月6日

  • ✓ 通过

    作者与仓库一致

    注册名称已通过 GitHub 账户 codeChap 验证,该账户拥有此仓库

  • … 尚未检查

    仍在维护

    我们还没有从 GitHub 读取这个仓库

  • … 尚未检查

    有许可证

    我们还没有从 GitHub 读取这个仓库

  • – 不适用

    端点有响应

    它在你的电脑上运行,没有互联网端点

  • – 不适用

    使用 OAuth 登录

    在你的电脑上运行,改用本地设置

  • … 尚未检查

    工具描述中没有隐藏指令

    它在你的电脑上运行;我们只能读取互联网端点的工具列表

与“其他”中的其他服务器比较i

  • 星标数多于此分类中其他 32455 个服务器的 0%
  • 发布到注册中心的时间比此分类中其他 32455 个服务器的 17% 更新
  • 基础检查结果等于或优于此分类中其他 32455 个服务器的 100%

与注册中心里这个分类中所有活跃的服务器比较。只有当发布者拥有该仓库时,星标数才计入。

常见问题

Fable 安全吗?

它在 1 项适用的基础检查中通过了 1 项。我们没有阅读代码。在添加密钥或令牌之前,请先看看这个服务器要求哪些权限,并使用只具备所需权限的密钥。

它需要哪些密钥或代码?

注册中心没有列出必需的密钥,不过有些服务器会在首次使用时要求你登录。

它在我的电脑上运行还是在云端?

它在你的电脑上运行。你的 AI 应用会在需要时启动它,数据不会经过作者的服务器(除非它自己调用在线服务)。

它还在维护吗?

GitHub 仓库最后更新于–,最新版本(0.1.0)于4个月前进入注册中心。

哪些应用可以使用它?

支持 MCP 的应用,例如 Claude Desktop、Claude Code、Cursor 和 VS Code。

有什么可以替代它?

同一分类中有:Spec Driven Development, Remote Desktop Commander, SSTracker free youth training

替代选择

同一分类中其他作者的服务器,按星标数排序。

如何看卡片:★ GitHub 星标i三大支柱:评价 · 检查 · 使用情况i更新 = 最新版本发布到注册中心的时间i

Spec Driven Development

作者:formulahendry

MCP Server that facilitates spec-driven development workflows, not just Vibe Coding.

在你的电脑上运行★ 440MIT14个月前更新
安装

Remote Desktop Commander

作者:desktop-commander

Remote Desktop Commander: use files, terminal and processes on your own computers from any AI app.

在云端运行★ 211昨天更新
安装

SSTracker free youth training

作者:sstracker.app

Free youth sports drills, practice plans and age-group answers for parents and coaches.

在云端运行今天更新
安装

作者的 README

打开 README

按原文从作者的仓库复制。PopNx MCP 没有审查或背书其内容。HTML、图片和脚本已被移除。链接会离开本站。

mcp-server-fable

An MCP (Model Context Protocol) server for Anthropic Claude Fable 5.1 — Anthropic's most capable, most expensive model ($10 / $50 per 1M input / output tokens, ~2× Opus). Built in Rust, it exposes Fable as specialized MCP tools (plan, critique, ask) so any MCP client can use them.

Fable is not a day-to-day chat model here. This server is built for the one thing that justifies the price: using Fable to plan and critique, then handing the result to a cheaper model (Sonnet / Haiku / Opus) to execute. It works in Claude Code, Claude Desktop, Cursor, custom agents, and any other environment that supports MCP servers over stdio.

Communicates via stdio using JSON-RPC 2.0. Structurally it mirrors mcp-server-claude-chat, but is deliberately adapted to Fable's API surface and purpose-built for the plan-then-execute pattern.

Why mcp-server-fable (vs. Claude Code's built-in advisor)?

Claude Code has a powerful native advisor feature (/advisor fable or the advisor tool). It lets a fast executor model (typically Sonnet or Haiku) dynamically ask Fable for guidance on hard decisions inside a single session.

This MCP server takes a complementary approach that is useful in more situations:

  • Explicit tools with handoff-optimized prompts — plan and critique use fixed, carefully written system prompts designed so the output can be passed *verbatim* to a cheaper model. Plans are numbered, unambiguous, include exact paths/signatures, edge cases, acceptance criteria, and out-of-scope notes. Critiques are deliberately coverage-first (report everything; filter downstream).
  • Works everywhere MCP works — Not limited to Claude Code. Use it in Claude Desktop, Cursor, Windsurf, custom agent frameworks, VS Code MCP extensions, scripts, or any future tool that supports the Model Context Protocol.
  • You control the orchestration — Call Fable for planning or review exactly when *you* (or your multi-agent system) decide, instead of relying on the model to escalate.
  • Clean composability — Treat Fable as a reusable specialist service alongside your other MCP servers. Perfect for modern "expensive model for judgment, cheap model for execution" workflows.
  • Correct Fable-specific behavior — Proper effort levels, refusal handling (no silent fallback), long timeouts, and accurate per-call cost reporting at Fable rates.

Many teams are converging on the same pattern the community discovered: use Fable narrowly for architecture, planning, and review, then execute with cheaper models. This server gives you first-class, portable tools for the "Fable parts" of that pattern.

See the "Technical details" section below for the specific Fable API differences that also required a dedicated implementation.

Subscription vs. API credits

This server uses the Anthropic API with an API key (API credits) — the only supported, terms-compliant way to drive Claude from a third-party tool. A Claude Pro/Max subscription is not usable here. Point base_url at an Anthropic-compatible gateway if you run one.

Technical details: Fable API differences

Fable's Messages API differs from the Opus-era shape (this is why a dedicated server was needed rather than reusing a general Claude chat wrapper):

  • No sampling parameters — temperature / top_p / top_k are rejected with a 400. There is no temperature tool argument.
  • Adaptive thinking only — reasoning is always on; depth is controlled by `effort` (low / medium / high / xhigh / max), not a token budget. The raw chain of thought is never returned; ask can request a readable *summary* via show_reasoning.
  • Refusals stop, cleanly — this is a *dedicated Fable server*. Fable's safety classifiers (cyber / bio / model-distillation) can decline a request; that comes back as a successful response with stop_reason: "refusal", surfaced with its category and explanation rather than as an answer. It is never silently retried on a different model.
  • 30-day data retention required — Fable is not available to zero-data-retention orgs; such orgs get a 400 on every request.

Every response also prints an estimated USD cost (at Fable's sticker rates), since cost-consciousness is the whole point.

Tools

ToolDescription
planFlagship. Turn a goal (+ optional context) into an executor-ready implementation plan: numbered steps, exact paths/signatures, edge cases, acceptance criteria, out-of-scope notes — written to be handed to a cheaper model and executed verbatim.
critiqueCoverage-first review of code, a diff, or a design. Reports every finding with severity + confidence for downstream filtering. Optional focus.
askRaw one-shot query to Fable. Multi-turn history, system prompt, effort, optional reasoning summary.
plan
NameTypeRequiredDescription
goalstringyesWhat to build or fix
contextstringnoRelevant code, file tree, constraints, error output, prior attempts
effortstringnolow/medium/high/xhigh/max (default high)
max_tokensintegernoMax tokens to generate (server default otherwise)
critique
NameTypeRequiredDescription
contentstringyesCode, diff, or design to review
focusstringnoArea to weight, e.g. security, concurrency
effortstringnolow/medium/high/xhigh/max (default high)
max_tokensintegernoMax tokens to generate
ask
NameTypeRequiredDescription
promptstringyesThe user message
system_promptstringnoSystem prompt
messagesstringnoHistory as a JSON array of {role, content} (roles user/assistant only)
effortstringnolow/medium/high/xhigh/max (default medium)
max_tokensintegernoMax tokens to generate
show_reasoningbooleannoReturn a summary of Fable's reasoning in a [thinking] block

Prerequisites

  • Rust (edition 2024)
  • An Anthropic API key from console.anthropic.com, on an org with ≥30-day data retention

The server expects a config file at ~/.config/mcp-server-fable/config.toml containing at minimum your api_key. See config.toml.example.

api_key = "sk-ant-..."

Optional overrides:

base_url = "https://api.anthropic.com/v1"

default_model = "claude-fable-5-1"

default_max_tokens = 8192

default_effort = "high" # low | medium | high | xhigh | max

The server fails fast at startup if the config is missing, api_key is empty, or default_effort (if set) is invalid.

Build

cargo build --release   # produces target/release/fable

cargo build # debug build cargo run # run in dev mode RUST_LOG=debug cargo run cargo test # unit tests (response formatting, cost, refusal, effort, message building)

Installation & MCP Configuration

1. Build the server
cargo build --release

The binary will be at: target/release/fable

Use the full absolute path to target/release/fable in all configuration below.

2. AI-assisted installation (recommended modern method)

Copy the block below and paste it directly to your AI coding assistant (Claude Code, Cursor, Grok, etc.). The AI will handle cloning (if needed), building, path resolution, and registration for you.

Add the mcp-server-fable MCP server for me.

Repository: https://github.com/ /mcp-server-fable (update this URL if you have a fork)

Steps to perform:

  1. If the repo isn't cloned locally yet, clone it and cd into it.
  2. Build the release binary: cargo build --release
  3. Determine the absolute path to the built binary (target/release/fable).
  4. Set up the config directory and file: mkdir -p ~/.config/mcp-server-fable cp config.toml.example ~/.config/mcp-server-fable/config.toml Then edit the config and add your Anthropic API key (api_key = "sk-ant-...").
  1. Register it as an MCP server named "fable".

For Claude Code, run: claude mcp add fable -- /target/release/fable

For Claude Desktop or other MCP clients, add this under the "mcpServers" key (use the real absolute path): { "fable": { "command": " /target/release/fable" } }

After setup, test that the plan tool is available and working.

3. Manual configuration

Claude Desktop or any MCP client (~/.config/Claude/claude_desktop_config.json or equivalent):

{

"mcpServers": { "fable": { "command": "/absolute/path/to/mcp-server-fable/target/release/fable" } } }

Claude Code (one-liner):

claude mcp add fable -- /absolute/path/to/mcp-server-fable/target/release/fable

Replace the path with your actual absolute path to the release binary.

Usage

Once it's registered, an MCP client calls the tools by name — the flagship is plan.

From an MCP client (e.g. Claude Code)

Ask the model to use it, handing over the goal plus whatever context the executor will need:

Use the fable plan tool. goal: "Add a --json flag to the CLI that prints results as JSON". context: "Rust clap app; output currently goes through println! in src/main.rs". effort: high

Claude Code issues a tools/call for plan; Fable returns a numbered, executor-ready plan — exact paths, signatures, edge cases, acceptance criteria — which you then hand to a cheaper model (Sonnet / Haiku) to implement verbatim.

Raw JSON-RPC over stdio

The same call without a client — a tools/call request the server reads on stdin:

{"jsonrpc":"2.0","id":2,"method":"tools/call","params":{

"name":"plan", "arguments":{ "goal":"Add a --json flag to the CLI that prints results as JSON", "context":"Rust clap app; output currently via println! in src/main.rs", "effort":"high" }}}

plan and critique return their content followed by a token + estimated-cost footer. Here is an actual response (from a tiny ask probe) showing that footer:

BINARY-OK

[stop_reason: end_turn] [tokens: 21 input + 9 output = 30 total] [cost: ≈ $0.0007 (fable rates)]

Because the server only ever calls Fable, that cost line is always at Fable's $10 / $50 per-1M rates — accurate by construction, not by convention.

Project Structure

src/

main.rs - entry point, config loading, stdio transport setup server.rs - MCP tool definitions (plan, critique, ask) + fixed prompts api.rs - Anthropic HTTP client, Effort enum, Messages types, refusal/cost formatter params.rs - tool parameter types with serde + JSON Schema derives config.rs - TOML config loading + effort validation

License

MIT

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