Spec Driven Development
MCP Server that facilitates spec-driven development workflows, not just Vibe Coding.
제작자가 쓴 설명(영어 원문)
Anthropic Claude Fable 5 MCP server — top-tier planning and code critique for handoff
이 세 가지는 절대 하나의 점수로 합치지 않아요. 의견, 측정, 인기는 서로 다른 것이니까요.
이 서버는 아직 쉬운 말로 된 요약을 쓰지 못했어요. 아래는 레지스트리에서 읽어 온 사실이에요.
쓰고 있는 AI 앱을 고른 다음 설정을 복사하세요.
제작자가 레지스트리에 설치 정보를 올리지 않았어요. 아래 제작자의 README를 확인하세요.
내 컴퓨터에서 실행돼요. 설치하면 AI 앱에 도구 목록이 나타나요.
누구나 볼 수 있는 정보를 점검했고, 코드는 읽지 않았어요. 해당하지 않는 항목은 개수에서 뺐어요. · 2026년 11월 7일 점검
레지스트리 이름이 GitHub 계정 codeChap 기준으로 확인되었고, 이 계정이 저장소를 소유하고 있어요
아직 GitHub에서 이 저장소를 읽어 오지 않았어요
아직 GitHub에서 이 저장소를 읽어 오지 않았어요
내 컴퓨터에서 실행되는 서버라 인터넷 엔드포인트가 없어요
내 컴퓨터에서 실행되며, 대신 로컬 설정을 사용해요
내 컴퓨터에서 실행돼요. 도구 목록은 인터넷 엔드포인트가 있는 서버에서만 읽을 수 있어요
레지스트리에서 이 카테고리의 활성 서버 전체와 비교했어요. 스타는 게시자가 저장소를 소유한 경우에만 세요.
해당하는 기본 점검 1개 중 1개를 통과했어요. 코드는 읽지 않았어요. 키나 토큰을 넣기 전에 서버가 어떤 권한을 요구하는지 확인하고, 꼭 필요한 권한만 있는 키를 쓰세요.
레지스트리에 필수 키가 나와 있지 않아요. 다만 처음 쓸 때 로그인을 요구하는 서버도 있어요.
내 컴퓨터에서 실행돼요. AI 앱이 필요할 때 실행하고, 데이터는 제작자의 서버를 거치지 않아요(서버 자체가 온라인 서비스를 호출하는 경우는 제외).
GitHub 저장소는 마지막으로 – 변경됐고, 최신 버전(0.1.0)은 4개월 전 레지스트리에 올라왔어요.
Claude Desktop, Claude Code, Cursor, VS Code처럼 MCP를 지원하는 앱에서 쓸 수 있어요.
같은 카테고리에는: Spec Driven Development, Remote Desktop Commander, Rystic
같은 카테고리에서 다른 제작자가 만든 서버예요. 스타 순으로 정렬했어요.
카드 보는 법:★ GitHub 스타i세 기둥: 리뷰 · 점검 · 사용 정도i업데이트 = 최신 버전을 레지스트리에 공개한 날i
MCP Server that facilitates spec-driven development workflows, not just Vibe Coding.
Remote Desktop Commander: use files, terminal and processes on your own computers from any AI app.
Start, seed, clock, inspect and diff Rystic API simulators from your agent.
제작자의 저장소에서 쓰인 그대로 가져왔어요. PopNx MCP가 검토하거나 보증한 내용이 아니에요. HTML, 이미지, 스크립트는 제거했어요. 링크를 누르면 이 사이트를 벗어나요.
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.
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:
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).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.
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.
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):
temperature / top_p / top_k are rejected with a 400. There is no temperature tool argument.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.stop_reason: "refusal", surfaced with its category and explanation rather than as an answer. It is never silently retried on a different model.Every response also prints an estimated USD cost (at Fable's sticker rates), since cost-consciousness is the whole point.
| Tool | Description |
|---|---|
plan | Flagship. 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. |
critique | Coverage-first review of code, a diff, or a design. Reports every finding with severity + confidence for downstream filtering. Optional focus. |
ask | Raw one-shot query to Fable. Multi-turn history, system prompt, effort, optional reasoning summary. |
| Name | Type | Required | Description |
|---|---|---|---|
goal | string | yes | What to build or fix |
context | string | no | Relevant code, file tree, constraints, error output, prior attempts |
effort | string | no | low/medium/high/xhigh/max (default high) |
max_tokens | integer | no | Max tokens to generate (server default otherwise) |
| Name | Type | Required | Description |
|---|---|---|---|
content | string | yes | Code, diff, or design to review |
focus | string | no | Area to weight, e.g. security, concurrency |
effort | string | no | low/medium/high/xhigh/max (default high) |
max_tokens | integer | no | Max tokens to generate |
| Name | Type | Required | Description |
|---|---|---|---|
prompt | string | yes | The user message |
system_prompt | string | no | System prompt |
messages | string | no | History as a JSON array of {role, content} (roles user/assistant only) |
effort | string | no | low/medium/high/xhigh/max (default medium) |
max_tokens | integer | no | Max tokens to generate |
show_reasoning | boolean | no | Return a summary of Fable's reasoning in a [thinking] block |
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-..."
The server fails fast at startup if the config is missing, api_key is empty, or default_effort (if set) is invalid.
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)
cargo build --release
Use the full absolute path to target/release/fable in all configuration below.
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:
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.
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.
Once it's registered, an MCP client calls the tools by name — the flagship is plan.
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
--jsonflag to the CLI that prints results as JSON". context: "Rustclapapp; output currently goes throughprintln!insrc/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.
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.
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
MIT