Spec Driven Development
MCP Server that facilitates spec-driven development workflows, not just Vibe Coding.
作者による説明(英語の原文)
Content-addressed semantics: fail-closed handshakes over 617 cognitive patterns.
この3つを1つのスコアにまとめることはしません。意見、測定、人気はそれぞれ別のものだからです。
このサーバーのやさしい解説はまだ書いていません。以下はレジストリから読み取った事実です。
使っているAIアプリを選んで、設定をコピーしてください。
必要なもの
どのアプリを使っていますか?
上でアプリを選んでください。選んだアプリを覚えておくので、次からはボタンに「…にインストール」と表示されます。
Claude Desktop → Settings → Developer → Edit Config を開き、claude_desktop_config.json にこれを貼り付けます
{
"mcpServers": {
"semahash": {
"command": "uvx",
"args": [
"semahash",
"mcp"
]
}
}
}ターミナルでこれを実行します
claude mcp add semahash -- uvx semahash mcpプロジェクトの .cursor/mcp.json、または ~/.cursor/mcp.json に貼り付けます
{
"mcpServers": {
"semahash": {
"command": "uvx",
"args": [
"semahash",
"mcp"
]
}
}
}ブラウザがアプリを開いてよいか確認し、そのあとアプリが設定を表示して確認を求めます。キーの値は空欄のままなので、自分で入力してください。
プロジェクトの .vscode/mcp.json に貼り付けます
{
"servers": {
"semahash": {
"type": "stdio",
"command": "uvx",
"args": [
"semahash",
"mcp"
]
}
}
}ブラウザがアプリを開いてよいか確認し、そのあとアプリが設定を表示して確認を求めます。キーの値は空欄のままなので、自分で入力してください。
これはパソコンで動くサーバーですが、ChatGPTがつなげるのはインターネット上のサーバーだけです。ほかのアプリを選んでください。
選んだアプリは、この端末のCookieに保存されます。アカウントは不要です。
この設定は、作者のレジストリ登録情報から作成しています。READMEと違う場合は、READMEに従ってください。
パソコンで動くサーバーです。インストールすると、ツール一覧がAIアプリに表示されます。
誰でも見られる情報をチェックしており、コードは読んでいません。当てはまらない項目は数に入れていません。 · 2026年11月7日にチェック
レジストリ名は、リポジトリを所有するGitHubアカウント emergent-wisdom で確認済みです
このリポジトリはまだGitHubから読み取っていません
このリポジトリはまだGitHubから読み取っていません
これはパソコンで動くため、インターネット上のエンドポイントはありません
パソコンで動き、代わりにローカルの設定を使います
パソコンで動くサーバーです。ツール一覧を読み取れるのは、インターネット上のエンドポイントがある場合だけです
レジストリでこのカテゴリにある有効なすべてのサーバーと比較しています。スターは、公開者がリポジトリの所有者である場合だけ数えます。
当てはまる基本チェック1項目のうち1項目に合格しました。コードは読んでいません。キーやトークンを追加する前に、サーバーがどんなアクセスを求めているかを確認し、必要な権限だけを持つキーを使ってください。
レジストリには必須のキーは載っていません。ただし、最初に使うときにサインインを求めるサーバーもあります。
あなたのパソコンで動きます。必要なときにAIアプリが起動し、データは作者のサーバーを通りません(サーバー自体がオンラインサービスを呼び出す場合を除きます)。
GitHubリポジトリの最終更新は–、最新バージョン(0.10.0)がレジストリに届いたのは27 日前です。
Claude Desktop、Claude Code、Cursor、VS CodeなどのMCP対応アプリで使えます。パソコンにPython (uv)も必要です。
同じカテゴリには:Spec Driven Development, Remote Desktop Commander, Master CSS
同じカテゴリで、ほかの作者が作ったサーバー。スターの多い順。
カードの見方:★ GitHubスターi3つの柱:レビュー · チェック · 利用状況i更新=最新バージョンをレジストリに公開した日i
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.
Inspect Master CSS classes, generated CSS, and project stylesheets from your AI client.
作者のリポジトリから書かれたとおりにコピーしたものです。PopNx MCPは内容を確認・推奨していません。HTML、画像、スクリプトは取り除いています。リンクはこのサイトの外へ移動します。
Content-addressed semantics for multi-agent coordination.
Sema is a content-addressed reference system for reasoning and communication. Participants encode and hash information under an agreed representation, then reuse the content address as a verifiable reference, optionally paired with a human-readable handle. Matching full references establishes identity of the resolved hashed content; semantic equivalence, correctness, and enforcement remain separate questions.
Web: semahash.org · Discord: Join
Add to any MCP client (Claude Code, Cursor, VS Code, Windsurf, Claude Desktop):
{
"mcpServers": { "sema": { "command": "uvx", "args": ["--from", "semahash[mcp]", "sema", "mcp"] } } }
Or via Claude Code CLI:
claude mcp add sema -- uvx --from "semahash[mcp]" sema mcp
This uses uv to download, install, and run sema in an isolated environment on first invocation, then caches it for subsequent calls.
Sema also ships as a Claude Code plugin — MCP server plus a skill that teaches the agent the search/resolve/mint/handshake workflow:
# One-time: add the Emergent Wisdom marketplace
claude plugin marketplace add emergent-wisdom/marketplace
claude plugin install sema
This gives you the MCP server and the sema-usage skill (auto-loaded), which teaches when to search vs mint, how to embed handles in text, and how to verify meaning at boundaries. The skill is a Claude Code convenience — the MCP server works with any client.
For local development:
claude --plugin-dir /path/to/sema
pip install "semahash[mcp]"
For CLI-only use (no MCP server):
pip install semahash
Already covered above via the JSON config or pip install path. For development against this repo:
git clone https://github.com/emergent-wisdom/sema.git
pip install -e "./sema[mcp]"
Your agent now has access to sema_search, sema_lookup, sema_handshake, and 9 more tools. Any MCP-compatible client works — Sema exposes a standard stdio server.
Verify it works — ask your agent: *"Search sema for coordination patterns and handshake on StateLock"*
Sema exposes a standard MCP stdio server — any MCP-compatible client works, including OpenClaw (openclaw mcp set sema '{"command":"uvx","args":["--from","semahash[mcp]","sema","mcp"]}').
# Search the vocabulary
sema search "coordination"
sema resolve StateLock
sema show StateLock
sema skeleton
sema serve --open
Build a private registry from scratch — no PR or maintainer in the loop:
sema init ./mylib.db
sema use ./mylib.db sema apply --add path/to/MyPattern.json sema search "..."
Subsequent sema commands (including sema mcp) read from your private registry. (SEMA_DB_PATH, if set, overrides sema use.) See CONTRIBUTING.md for the canonical contribution path and docs/specification/versioning.md for the refinement and supersession policy.
Package a project database as a verified, standalone library release:
sema package ./mylib.db \
--name mylib \ --version 1.0.0 \ --output-dir dist/mylib-1.0.0 \ --github-repo acme/sema-mylib
Publish the generated library.json and versioned ZIP as assets on the corresponding published GitHub Release. Consumers install the Release asset URL for library.json—not the repository URL or a branch:
sema install https://github.com/acme/sema-mylib/releases/latest/download/library.json
sema use mylib sema list sema root
It installs one verified snapshot at a time rather than merging vocabularies; the bundled vocabulary remains the offline default. Use sema update mylib to follow the installed library's recorded release pointer. See Publishing and Installing Vocabulary Libraries for the complete DeFi authoring, dependency-closure, packaging, GitHub Release, and update workflow.
Libraries published on semahash.org can be found and installed by name, without an account:
sema registry search defi
sema install mylib
To list a release there so other people and agents can find it, log in once and publish from the command line:
sema login # approve the short code in your browser, once
sema registry import https://github.com/acme/sema-mylib/releases/latest/download/library.json
An agent can log in with a key that you create on your semahash.org profile page instead: it pipes the key to sema login --key - or calls the sema_library_login MCP tool.
The login follows the OAuth 2.0 device authorization flow, so it also works from an agent or a machine without a browser. To use another deployment, run sema login --registry https://registry.example. A successful login remembers that registry for subsequent commands. --registry and SEMA_REGISTRY_URL override the remembered choice; https://semahash.org is the first-use default.
from sema.core.registry import RegistryManager
registry = RegistryManager() pattern = registry.get_pattern("StateLock")
print(pattern["sema_ref"]) # StateLock#c9c2
assert pattern["sema_ref"] == "StateLock#c9c2"
python experiments/demos/local_handshake.py
See the handshake in action: matching hashes PROCEED, mismatched hashes HALT, and unknown patterns HALT. Cooperative mode accepts short prefixes for drift detection; strict mode requires the full hash. Takes 2 seconds.
word = hash(canonical(definition))
Take any concept (a coordination protocol, a reasoning pattern, a trust mechanism), express it in canonical form, hash it. That hash IS the word. Change one byte in the definition, get a different word.
Cooperative: sema_handshake("StateLock#c9c2")
-> PROCEED with assurance="prefix", or HALT
Strict: sema_handshake("StateLock", " ", strict=true) -> PROCEED with assurance="full_hash", or HALT
This is the Anti-Postel principle: strict mode proceeds only on full-hash identity; cooperative mode uses compact prefixes as a non-adversarial drift signal. Mismatches fail closed in both modes.
The bundled vocabulary spans 4 layers:
Each pattern is a content-addressed behavioral definition. Concrete cards may add machine-verifiable contracts, invariants, failure modes, parameters, and typed dependencies where those fields are identity-defining.
When running as an MCP server (sema mcp), these tools are available:
| Tool | Description |
|---|---|
sema_search | Search patterns by name, description, or meaning |
sema_lookup | Get a pattern by its reference (e.g., StateLock#c9c2) |
sema_resolve | Get a pattern with dependencies expanded |
sema_handshake | Fail-closed semantic verification between agents |
sema_mint | Create a new pattern (validate, hash, add to vocabulary) |
sema_propose_context | Compute a context digest for a multi-agent definition set (drift detection) |
sema_verify_context | Verify a context proposal from another agent |
sema_tree | Browse vocabulary by layer and category |
sema_validate | Validate a pattern JSON for correctness |
sema_stats | Vocabulary statistics |
sema_graph_skeleton | Ultra-minimal graph overview (~150 tokens) |
sema_reset_session | Clear session cache so searches return full results again |
sema_library_search | Find libraries published on semahash.org |
sema_library_install | Verify and install a library by name or library.json URL |
sema_library_login | Store a semahash.org key that the user gives the agent |
sema_library_publish | Publish a GitHub release on semahash.org, after the user agrees |
pip install "semahash[api]"
sema serve --open
The local view shows the vocabulary selected with sema use, the same one a connected agent writes to. It follows later switches, and its 3D graph grows while the agent mints: new patterns light up and appear in a live list. The pattern browser has card, list, and JSON views. Development stays on your computer; semahash.org hosts finished libraries, and a writable vocabulary's page lists the optional steps to publish one there.
The experiments/ directory contains reproducible evaluations of Sema's claims and implementation boundaries.
The public v0.3.0 to v0.4.0 reconstruction experiment checks whether the current graph and hash-cascade algorithm can rebuild a target vocabulary from an earlier release. It compares both aggregate roots, semantic pattern content, the logical dependency graph, unhashed metadata, and the complete normalized read model rather than treating root equality as complete release equality. It also demonstrates the safe reconstruction path: integrate the delta into a complete staged card snapshot, compile a fresh database, verify the result, and only then activate it.
.venv/bin/python experiments/delta_reconstruction/reproduce.py
The experiment and its expected results are documented in experiments/delta_reconstruction/README.md. Small synthetic versions of its addition, removal, rename, cascade, metadata, and failure cases run in the regular test suite.
The controlled multi-agent design challenge compares three conditions:
| Condition | Sema | Turns | Outcome |
|---|---|---|---|
| A: Natural language only | No | 4 | Design rejected |
| B: Sema vocabulary | Yes | 11 | SAD Engine approved |
| C: Sema + protocol | Yes | 25 | SAD Engine with exhaustive vetting |
Agents with Sema patterns produced physics-grounded designs that survived adversarial scrutiny. Agents without Sema produced shallow designs that failed safety review.
To reproduce:
`bas
冒頭だけを表示しています。続きはリポジトリで読めます