# Sema: When the Hash Is the Word **Content-addressed semantics for multi-agent coordination.** [](https://pypi.org/project/semahash/) [](https://registry.modelcontextprotocol.io/servers/io.github.emergent-wisdom/semahash) [](https://github.com/emergent-wisdom/sema/blob/main/paper/sema.pdf) [](https://doi.org/10.5281/zenodo.19462702) [](https://github.com/emergent-wisdom/sema/blob/main/LICENSE) [](https://github.com/emergent-wisdom/sema/blob/main/LICENSE-CONTENT) 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](https://semahash.org) · **Discord:** [Join](https://discord.gg/hRhVqAuDYQ) ## Install ### MCP Server (recommended) Add to any MCP client (Claude Code, Cursor, VS Code, Windsurf, Claude Desktop): ```json { "mcpServers": { "sema": { "command": "uvx", "args": ["--from", "semahash[mcp]", "sema", "mcp"] } } } ``` Or via Claude Code CLI: ```bash claude mcp add sema -- uvx --from "semahash[mcp]" sema mcp ``` This uses [uv](https://docs.astral.sh/uv/) to download, install, and run sema in an isolated environment on first invocation, then caches it for subsequent calls. ### Claude Code plugin (MCP server + skill) Sema also ships as a Claude Code plugin — MCP server plus a skill that teaches the agent the search/resolve/mint/handshake workflow: ```bash # One-time: add the Emergent Wisdom marketplace claude plugin marketplace add emergent-wisdom/marketplace # Install the plugin 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: ```bash claude --plugin-dir /path/to/sema ``` ### Permanent install (pip) ```bash pip install "semahash[mcp]" ``` For CLI-only use (no MCP server): ```bash pip install semahash ``` ## Quick Start ### Use with AI Agents (MCP) Already covered above via the JSON config or `pip install` path. For development against this repo: ```bash 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](https://openclaw.ai/) (`openclaw mcp set sema '{"command":"uvx","args":["--from","semahash[mcp]","sema","mcp"]}'`). ### Use via CLI ```bash # Search the vocabulary sema search "coordination" # Look up a specific pattern sema resolve StateLock # Print a pattern's full definition sema show StateLock # Browse the graph structure sema skeleton # Start local API + web frontend (binds to 127.0.0.1 by default) sema serve ``` ### Bring Your Own Vocabulary Build a private registry from scratch — no PR or maintainer in the loop: ```bash 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](CONTRIBUTING.md) for the canonical contribution path and [docs/specification/versioning.md](docs/specification/versioning.md) for the refinement and supersession policy. Package a project database as a verified, standalone library release: ```bash 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: ```bash 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](docs/guides/libraries.md) for the complete DeFi authoring, dependency-closure, packaging, GitHub Release, and update workflow. ### Use in Python ```python from sema.core.registry import RegistryManager registry = RegistryManager() pattern = registry.get_pattern("StateLock") # Look up the canonical reference print(pattern["sema_ref"]) # StateLock#c9c2 # Verify an inline reference before relying on it assert pattern["sema_ref"] == "StateLock#c9c2" ``` ### Try the Protocol (No API Keys Needed) ```bash 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. ## How It Works ``` 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 Vocabulary The bundled vocabulary spans 4 layers: - **Physics** — Immutable substrate (locks, entropy, causality) - **Mind** — Hybrid cognition (reasoning, inference, strategy) - **Society** — Multi-agent coordination (economics, governance, protocols) - **Infrastructure** — Operational constraints (data structures, verification) 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. ## MCP Tools 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 | ## Web Frontend ```bash pip install "semahash[api]" sema serve # Open http://localhost:3000 ``` Interactive 3D graph visualization, pattern browser, and search. Built with React + Three.js. ## Experiments The `experiments/` directory contains reproducible evaluations of Sema's claims and implementation boundaries. ### Delta reconstruction 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. ```bash .venv/bin/python experiments/delta_reconstruction/reproduce.py ``` The experiment and its expected results are documented in [`experiments/delta_reconstruction/README.md`](experiments/delta_reconstruction/README.md). Small synthetic versions of its addition, removal, rename, cascade, metadata, and failure cases run in the regular test suite. ### Multi-agent design challenge 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: ```bash cd experiments/sema_design_challenge export GOOGLE_API_KEY=your_key ./reproduce.sh ``` See [`experiments/sema_design_challenge/README.md`](experiments/sema_design_challenge/README.md) for details. ## Key Properties - **Zero semantic collisions** across the full vocabulary - **16.9x average token compression** via content-addressed stubs - **Fail-closed architecture** — mismatches halt, never fail silently - **Mean embedding similarity of 0.21** — high structural distinctness ### Formal-verification pilot Sema's handshake decision kernel and canonicalization type tags have a small Lean 4 proof suite. The handshake supports cooperative prefix matching for ordinary drift detection and strict full-hash verification for proof-grade identity; the proofs state each guarantee separately. The encoding proof establishes pre-hash domain separation, while Python conformance tests connect the models to production. See [`verification/README.md`](verification/README.md) for the proven theorems, trusted-computing-base assumptions, and explicit limits of the claim. ## Using with understanding-graph Sema gives your agents shared *semantic* memory — a vocabulary of cognitive patterns with content-addressed identity. [Understanding Graph](https://github.com/emergent-wisdom/understanding-graph) gives them shared *episodic* memory — the actual thinking trail behind a decision. They compose: ```bash claude mcp add sema -- uvx --from "semahash[mcp]" sema mcp claude mcp add ug -- npx -y understanding-graph mcp ``` With both installed, an agent can: 1. Anchor an understanding-graph decision node in a sema pattern hash (e.g. `StateLock#c9c2`) so the meaning of the primitive can never drift. 2. Use `graph_semantic_search` to find all past graph nodes that reference a given sema pattern — hash-stable history, not keyword matching. 3. Call `sema_handshake` *before* writing a decision that depends on a shared concept; if it returns `HALT`, the agent writes a `tension` node instead and stops, preventing silent divergence. Full walkthrough: [docs/guides/understanding-graph.md](docs/guides/understanding-graph.md) ## Repository Structure ``` sema/ ├── src/sema/ Core library (hashing, validation, MCP server, API) ├── data/ Vocabulary pattern cards + taxonomy databases ├── docs/ Documentation (philosophy, schema spec, CLI reference) ├── paper/ Academic paper (sema.tex) ├── web/ Web frontend (React + Three.js graph visualization) ├── experiments/ │ ├── orchestrator/ Multi-agent engine (bundled for experiment reproduction) │ ├── delta_reconstruction/ Historical release reconstruction validation │ ├── sema_design_challenge/ Main experiment (3 conditions, 5 runs, full traces) │ └── demos/ Standalone demos (local handshake, Babel Test) └── pyproject.toml Package config (extras: [mcp], [api], [full]) ``` ## Contributing Want to add patterns, improve existing ones, or host the frontend locally? See [CONTRIBUTING.md](CONTRIBUTING.md). ## Citing ```bibtex @misc{westerberg2026sema, title = {Sema: When the Hash Is the Word}, author = {Westerberg, Henrik}, year = {2026}, month = apr, publisher = {Zenodo}, doi = {10.5281/zenodo.19462702}, url = {https://doi.org/10.5281/zenodo.19462702} } ``` See [`CITATION.cff`](CITATION.cff) for the machine-readable version (GitHub renders a "Cite this repository" button from it). ## Safety Sema ships no executable code — it's a library of pattern *definitions* (handles, mechanisms, invariants, dependency graphs). The MCP server hands patterns to clients as data; it does not execute the behaviors they describe. **Intended use: reasoning and reference.** Patterns are thinking tools — named concepts agents can search, resolve, and handshake on to reason about coordination, risk, and procedure. See [`docs/manuals/vocabulary-design.md`](docs/manuals/vocabulary-design.md) for the intent behind each pattern and the design choices. **Running patterns as executable recipes is untested.** Many patterns describe procedures an agent could step through. That path is still a research phase — the mechanism text has not been validated end-to-end, and we make no claims about safety when a pattern is executed rather than referenced. If you go this route, run the agent's execution step in a sandboxed environment. Patterns with known risks carry a `caution` field in their metadata; absence of that flag means the pattern has not been classified as risky, not that it has been certified safe. The long-term goal is cryptographically enforced safety constraints on agent-to-agent communication — an active research direction. ## License Sema is dual-licensed: - **Code** (everything in `src/`, `web/`, `experiments/`, `scripts/`, and the package config) — [MIT](LICENSE). Self-host it, fork it, build commercial products on top of it. - **Content** (the pattern vocabulary in `data/`, the documentation in `docs/`, the academic paper in `paper/`, and the prose displayed on [semahash.org](https://semahash.org)) — [CC BY 4.0](LICENSE-CONTENT). Reuse the patterns and prose anywhere, for any purpose including commercial, as long as you attribute Henrik Westerberg. For academic citation, see [`CITATION.cff`](CITATION.cff). GitHub renders this as a "Cite this repository" button on the project page that generates APA and BibTeX automatically.