Spec Driven Development
MCP Server that facilitates spec-driven development workflows, not just Vibe Coding.
제작자가 쓴 설명(영어 원문)
Content-addressed semantics: fail-closed handshakes over 617 cognitive patterns.
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.
필요한 것
어떤 앱을 쓰세요?
위에서 앱을 고르세요. 기억해 두었다가 다음부터는 버튼에 “…에 설치”라고 표시해요.
Claude Desktop → Settings → Developer → Edit Config를 열고 claude_desktop_config.json에 이 내용을 붙여 넣으세요
{
"mcpServers": {
"semahash": {
"command": "uvx",
"args": [
"semahash",
"mcp"
]
}
}
}터미널에서 이 명령어를 실행하세요
claude mcp add semahash -- uvx semahash mcp프로젝트의 .cursor/mcp.json 또는 ~/.cursor/mcp.json에 붙여 넣으세요
{
"mcpServers": {
"semahash": {
"command": "uvx",
"args": [
"semahash",
"mcp"
]
}
}
}브라우저가 앱을 열지 물어본 다음, 앱이 설정을 보여 주고 확인을 요청해요. 키 값은 비워 두니 직접 입력하세요.
프로젝트의 .vscode/mcp.json에 붙여 넣으세요
{
"servers": {
"semahash": {
"type": "stdio",
"command": "uvx",
"args": [
"semahash",
"mcp"
]
}
}
}브라우저가 앱을 열지 물어본 다음, 앱이 설정을 보여 주고 확인을 요청해요. 키 값은 비워 두니 직접 입력하세요.
이 서버는 내 컴퓨터에서 실행되는데, ChatGPT는 인터넷에 있는 서버에만 연결할 수 있어요. 다른 앱을 고르세요.
선택한 앱은 이 기기의 쿠키에만 저장돼요. 계정은 필요 없어요.
이 설정은 제작자의 레지스트리 정보로 만들었어요. README와 다르면 README를 따르세요.
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 emergent-wisdom 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(0.10.0)은 27일 전 레지스트리에 올라왔어요.
Claude Desktop, Claude Code, Cursor, VS Code처럼 MCP를 지원하는 앱에서 쓸 수 있어요. 내 컴퓨터에 Python (uv)도 있어야 해요.
같은 카테고리에는: Spec Driven Development, Remote Desktop Commander, Systemdox
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.
Your architecture in your agents' context: checks, specs, ADRs and docs over MCP, at write time.
제작자의 저장소에서 쓰인 그대로 가져왔어요. PopNx MCP가 검토하거나 보증한 내용이 아니에요. HTML, 이미지, 스크립트는 제거했어요. 링크를 누르면 이 사이트를 벗어나요.
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
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