Spec Driven Development
MCP Server that facilitates spec-driven development workflows, not just Vibe Coding.
Descripción del creador (original en inglés)
Content-addressed semantics: fail-closed handshakes over 617 cognitive patterns.
Estos tres nunca se combinan en una sola puntuación: las opiniones, las mediciones y la popularidad son cosas distintas.
Todavía no escribimos un resumen sencillo para este. Abajo están los datos que leímos del registro.
Elige la app de IA que usas y copia la configuración.
Necesitas
¿Qué app usas?
Elige tu app arriba. La recordamos, así que la próxima vez el botón dirá “Instalar en …”.
Abre Claude Desktop → Settings → Developer → Edit Config y pega esto en claude_desktop_config.json
{
"mcpServers": {
"semahash": {
"command": "uvx",
"args": [
"semahash",
"mcp"
]
}
}
}Ejecuta esto en tu terminal
claude mcp add semahash -- uvx semahash mcpPégalo en .cursor/mcp.json de tu proyecto, o en ~/.cursor/mcp.json
{
"mcpServers": {
"semahash": {
"command": "uvx",
"args": [
"semahash",
"mcp"
]
}
}
}Tu navegador te pide permiso para abrir la app; luego la app muestra la configuración y te pide confirmar. Los valores de las claves quedan vacíos para que los completes tú.
Pégalo en .vscode/mcp.json de tu proyecto
{
"servers": {
"semahash": {
"type": "stdio",
"command": "uvx",
"args": [
"semahash",
"mcp"
]
}
}
}Tu navegador te pide permiso para abrir la app; luego la app muestra la configuración y te pide confirmar. Los valores de las claves quedan vacíos para que los completes tú.
Este se ejecuta en tu computadora, y ChatGPT solo puede conectarse a servidores en internet. Elige otra app.
Tu elección se guarda en una cookie en este dispositivo; no necesitas cuenta.
Esta configuración se genera a partir de la ficha del creador en el registro. Si el README dice otra cosa, sigue el README.
Se ejecuta en tu computadora; la lista de herramientas aparece en tu app de IA después de instalarlo.
Revisamos información que cualquiera puede ver; no hemos leído el código. Las revisiones que no aplican no se cuentan. · Revisado el 7 nov 2026
El nombre en el registro se verificó con la cuenta de GitHub emergent-wisdom, dueña del repo
Todavía no hemos leído este repo en GitHub
Todavía no hemos leído este repo en GitHub
Este se ejecuta en tu computadora; no hay endpoint en internet
Se ejecuta en tu computadora y usa ajustes locales en su lugar
Se ejecuta en tu computadora; solo podemos leer listas de herramientas de endpoints en internet
Comparado con todos los servidores activos de esta categoría en el registro. Las estrellas solo cuentan cuando quien lo publica es dueño del repo.
Superó 1 de 1 revisiones básicas aplicables. No hemos leído el código. Antes de agregar una clave o un token, revisa qué acceso pide el servidor y usa una clave que tenga solo los permisos que necesitas.
El registro no indica ninguna clave obligatoria, aunque algunos servidores te piden iniciar sesión la primera vez que los usas.
Se ejecuta en tu computadora. Tu app de IA lo inicia cuando hace falta, y los datos no pasan por los servidores del creador (a menos que el propio servidor llame a un servicio en línea).
El repo de GitHub cambió por última vez –, y la última versión (0.10.0) llegó al registro hace 27 días.
Las apps compatibles con MCP, como Claude Desktop, Claude Code, Cursor y VS Code. También necesitas Python (uv) en tu computadora.
En la misma categoría: Spec Driven Development, Remote Desktop Commander, Master CSS
Servidores de la misma categoría hechos por otros creadores, ordenados por estrellas.
Cómo leer una tarjeta:★ Estrellas de GitHubiTres pilares: reseñas · revisiones · usoiActualizado = fecha en que se publicó la última versión en el registroi
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.
Copiado tal cual del repo del creador. PopNx MCP no lo ha revisado ni lo respalda. Se quitaron HTML, imágenes y scripts. Los enlaces llevan fuera de este sitio.
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
Solo se muestra el principio; lee el resto en el repo