HAI-MCP

HAI-MCP · Model-agnostic MCP control-plane for the Human Agent Interface (HAI) approach

---

Why this repo exists

Agents are now driving shells, editors, browsers, and CI. Most of them work without a human in the loop long enough for the human to lose the thread. HAI — the Human Agent Interface — is an opinionated, evidence-based way to keep agentic work observable, bounded, owner-gated, and recoverable so a human can still own the work even when an agent is doing it.

HAI-MCP is the open-source, model-agnostic implementation of that approach. It is one of the pieces of Samuel Fleig's HAI stack — the part that any Model-Context-Protocol-speaking client can talk to, regardless of which LLM sits behind it.

Canonical site: https://www.human-agent-interface.com/ · About Samuel: https://www.human-agent-interface.com/samuel/

---

What "MCP control-plane" means here

MCP — the Model Context Protocol — is a standard JSON-RPC interface that lets a tool server expose tools, resources, and prompts to an LLM-backed client (Claude Code, Codex, Cursor, Grok, OpenCode, Hermes, …). The client discovers the server's tools and calls them during a conversation; the server stays stateless from the model's point of view.

A control-plane server is one that does not do the work itself — it governs how work is authorised, scoped, recorded, and handed back to the human. Concretely, an MCP control-plane:

Concern	What HAI-MCP exposes for it
Mission contract	hai_open_mission, hai_get_contract, hai_recontract
Session leasing	hai_authorize_session — time-bounded, contract-versioned
Activity classification	hai_check_activity / hai_drift_check — on-contract vs. off-contract
Focus & lanes	hai_set_focus, hai_status — at most 2 ACTIVE lanes
Owner gate	one-time nonces out-of-band (HAI_OWNER_HOME or ntfy) for accept / recontract / abandon
Evidence & closure	hai_proof, hai_close_mission, hai_stop
Inbox & intake	hai_intake, hai_distill, hai_park, hai_park_item
Recovery	hai_checkpoint, hai_recover

HAI-MCP is deliberately not an agent runtime. It never calls an LLM, never runs shell, never pushes to git, and never deletes files. It is the judge — agents call it to ask "may I?" and to record "I did".

---

Features

• One state engine, 23 tools — three surfaces (legacy control plane, mission lifecycle, daily-loop wrappers) sharing one hardened core.
• Strict fail-closed boundary — inputs are typed and rejected, not coerced. A String "2" is refused for an Integer field; the server stays reachable instead of silently mangling types.
• Versioned mission contracts — every mission has a contract with a monotonic version. Recontracting produces a visible field-level diff and revokes every existing lease.
• Time-bounded session leases — hai_authorize_session binds a lease to a mission id, a contract version, a duration, a role, a contribution, and a claimed criterion set.
• Deterministic drift check — hai_check_activity classifies planned or observed activity against the contract without ever calling an LLM.
• Two-principal owner gate:
  • Default (nonce): the server delivers a one-time code to the owner channel (HAI_OWNER_HOME/file or ntfy). The client never sees the code. The code is bound to the exact change, single-use, expiring; only the hash is stored in HAI_HOME.
  • ack_legacy: the old self-asserted owner_ack flag — an honor system, surfaced as such by hai_health.
• Mount table — hai_bind_project joins a logical project_id to a device-local directory behind owner_ack + reason.
• Model-agnostic — same binary, same tools, same contract. Switch LLMs without rewriting governance.
• Two transports — stdio (default) and streamable-http with optional bearer-token binding (loopback only by default).
• Checkpoint & recover — hai_checkpoint snapshots context; hai_recover returns the smallest recovery next action.
• 139 tests green — the engine is covered; the slice remains open for the learning-budget and owner-instrument follow-ups.

---

Install & run

Requires Python ≥ 3.12 and uv.

git clone https://github.com/smlfg/hai-mcp.git
cd hai-mcp
uv sync --all-extras
uv run hai-mcp          # stdio transport, default

Streamable-HTTP transport:

HAI_TRANSPORT=streamable-http \
HAI_HTTP_HOST=127.0.0.1 \
HAI_HTTP_PORT=8765 \
HAI_HTTP_TOKEN="$(openssl rand -hex 32)" \
uv run hai-mcp

HTTP binding to non-loopback hosts is refused unless HAI_HTTP_TOKEN is set. See docs/OWNER_GATE.md and the --help output.

---

Sample usage — wiring the server into a client

The server is transport-agnostic; every MCP client gets the same 23 tools. Drop the snippet into the client's MCP config and restart.

Claude Code / Claude Desktop

{
  "mcpServers": {
    "hai": {
      "command": "uv",
      "args": [
        "run",
        "--directory",
        "/absolute/path/to/hai-mcp",
        "hai-mcp"
      ],
      "env": {
        "HAI_HOME": "/home/you/.hai",
        "HAI_OWNER_HOME": "/home/you/.hai-owner"
      }
    }
  }
}

Cursor

{
  "mcpServers": {
    "hai": {
      "command": "uv",
      "args": [
        "run",
        "--directory",
        "/absolute/path/to/hai-mcp",
        "hai-mcp"
      ],
      "env": {
        "HAI_HOME": "/home/you/.hai",
        "HAI_OWNER_HOME": "/home/you/.hai-owner"
      }
    }
  }
}

Codex / Hermes / any MCP stdio client

Same shape — point at the uv run --directory … hai-mcp command and pass the two env vars. More snippets live in docs/client-snippets/.

---

Sample usage — driving the protocol

A typical agent loop calls HAI-MCP before it acts and after it acts.

1. Open a bounded mission

hai_mission_start(
  problem   = "Refactor the evaluator harness to be deterministic.",
  artifact  = "Pull request titled 'evaluator: deterministic harness'.",
  done_criteria = [
    {"id": "C1", "description": "Two A/B cases produce identical verdicts on three reruns."},
    {"id": "C2", "description": "Harness runs offline; no live network calls."},
  ],
  owner             = "samuel",
  time_limit_hours  = 6,
  non_goals         = ["Do not touch the MCP server.", "Do not change contract shapes."],
  constraints       = {"python": ">=3.12", "branch": "slice/eval-determinism"},
)

2. Authorise a session lease

hai_authorize_session(
  mission_id         = "<from open>",
  contract_version   = 1,
  agent_identity     = "codex-cli",
  role               = "implementer",
  contribution       = "Deterministic A/B harness",
  expected_result    = "Green pytest with frozen inputs.",
  duration_minutes   = 90,
  criterion_ids      = ["C1", "C2"],
  device_id          = "mbp-mirgraatin",
  harness_id         = "codex-cli/0.45",
)

3. Check an activity before running it

hai_check_activity(
  session_id     = "<from lease>",
  activity_step  = "Replace random.seed with a seeded fixture in tests/test_eval_ab.py",
  criterion_id   = "C1",
  affected_paths = ["tests/test_eval_ab.py", "tests/fixtures/ab/case1.json"],
)
# → {"verdict": "on_contract", ...}

4. Close with evidence

hai_proof(
  mission_id        = "<from open>",
  contract_version  = 1,
  outcome_summary   = "A/B cases produce identical verdicts on three reruns; harness offline.",
  evidence          = {
    "C1": {"command": "pytest tests/test_eval_ab.py -q", "exit_code": 0,
           "reruns": [0, 0, 0]},
    "C2": {"command": "pytest tests/test_eval_ab.py -q --offline", "exit_code": 0},
  },
)

5. Owner-gated promotion

For hai_accept_next_step, hai_recontract, or abandoning a mission, the first call without owner_code delivers a one-time code to the owner's channel (the file sink in HAI_OWNER_HOME, or an ntfy topic). Relaying that code back as owner_code=<code> completes the action. The code is bound to the exact change, single-use, and only its hash is persisted in HAI_HOME. Detail: docs/OWNER_GATE.md.

---

State layout

• Global: $HAI_HOME — default ~/.hai
• Owner channel: $HAI_OWNER_HOME — default ~/.hai-owner (deliberately outside HAI_HOME so the agent cannot read it)
• Per-project: <project_path>/Projek-Managment/ (legacy) or device mount + relative prefixes when a project_id is bound
• Mount table: HAI_HOME/core/projects.json

All writes are resolved and confined to these roots.

---

Project layout

hai-mcp/
├── docs/
│   ├── TOOL_CONTRACT.md      # normative tool contract (gates, errors, schemas)
│   ├── OWNER_GATE.md         # nonce + ack_legacy owner-gate spec
│   ├── BUILD_HANDOFF.md
│   ├── client-snippets/      # ready-to-paste mcp.json snippets
│   ├── eval/                 # A/B harness contract
│   ├── plans/                # dated design slices
│   └── visuals/              # mission-lifecycle banner assets
├── scripts/                  # stdio smoke + impact-eval runner
├── src/hai_mcp/              # the server
└── tests/                    # 139 tests

---

Limitations

HAI-MCP is intentionally narrow. It does not:

• Call any LLM. The server is dumb on purpose — governance is a separate concern from generation.
• Execute code, run shells, push git, or delete files. It refuses tools like "commit & push", "run pytest", "rm -rf". Agents are expected to do those things and report back via hai_check_activity / hai_proof.
• Merge with hai-intake packages. The intake pipeline is a separate stack; coexistence is fine, fusion is not.
• Provide a UI. There is no dashboard. The control plane speaks MCP and writes JSON; visualisation is the client's job.
• Multi-mission concurrency. Exactly one active mission globally. Open a new one only after the previous is closed (completed or abandoned).
• Cross-device writes. Each device sees only its own mounts. The mount table is per-device; the contract is global.
• Forward compatibility for major MCP bumps. The server pins mcp>=1.9.0,<2; a v2 of MCP will require a separate migration slice.
• No revocation list / no kill-switch API. Lease invalidation happens via recontract, mission close, or hai_stop; there is no out-of-band "revoke everything right now" tool.
• No automatic recovery from a corrupted HAI_HOME. If the global state directory is corrupted, the server fails closed — by design, but recovery is manual (see hai_recover).

See docs/TOOL_CONTRACT.md for the full gate matrix and docs/OWNER_GATE.md for the owner-gate contract.

---

Tests

uv run pytest                       # full suite
uv run python scripts/stdio_smoke.py  # stdio round-trip smoke

The repo carries 139 green tests as of the 0.1.0 slice. CI status lives on the GitHub Actions page of the repository.

---

Contributing

The control plane is small on purpose — additions go through a contract slice:

1. Read docs/TOOL_CONTRACT.md.
2. Open an issue describing the tool / gate / state change.
3. Land it behind a fail-closed slice with tests + plan in docs/plans/.

Pull requests that change gates, schemas, or the mount table without a matching plan will be asked to follow the same path.

---

License

MIT — see LICENSE. Copyright © 2026 Samuel Fleig.

---

Acknowledgements

HAI-MCP is one piece of Samuel Fleig's HAI stack. It stands on:

• the Model Context Protocol specification,
• the mcp Python SDK (mcp>=1.9.0,<2),
• and the legacy ~/.config/hai-agent-mcp Hermes bridge that this server replaces for control-plane work. Coexistence is supported; the bridge is not required.

Canonical HAI site: https://www.human-agent-interface.com/ · About Samuel Fleig: https://www.human-agent-interface.com/samuel/