Watchlight — Developer Edition

Govern an AI agent in five minutes. One install, zero infrastructure, same API as production.

Watchlight is an Agent Runtime Governance Control Plane — it puts a policy decision point in front of every action your AI agents take, authorizing tool calls and recording a tamper-evident, value-free audit trail.

The Developer Edition is the free, open front door to it. It runs the real authorization engine in-process, so you can add a governed ALLOW / DENY to your agent on your own laptop — no server, no database, no signup. It's for evaluating the model and shipping governed agents; the code you write here is the code you run in production — going to production is pointing the same code at the running control plane, not a rewrite.

For enterprises, Watchlight provides the wider Agent Runtime Governance Control Plane: signed, tamper-evident lineage; multi-tenant isolation; drift & anomaly detection → automatic quarantine; and fleet-wide revocation across every agent and environment. → watchlight.ai

How the pieces fit together

             your code · agents · tools
  ┌─────────────┬──────────────────┬──────────────┬─────────────┐
  │ @govern.tool│  LangGraph /     │  MCP client  │  custom app │
  │ (decorator) │  Pydantic AI /   │  (any tool)  │             │
  │             │  Claude Agent    │              │             │
  └──────┬──────┴────────┬─────────┴──────┬───────┴──────┬──────┘
         │               │                │              │
     watchlight   watchlight.<fw>   watchlight-mcp    watchlight
      (govern)   .governed_plugin   (PEP · MCP spec)     SDK
         └───────────────┴───────┬────────┴──────────────┘
                                 ▼
                 ┌───────────────────────────────┐
                 │  Watchlight engine · Cedar     │   the REAL engine,
                 │  in-process · zero infra       │   a compiled wheel
                 └───────────────┬───────────────┘
                PERMIT ─ forward │ ─ DENY  (blocked before execution)
                                 ▼
              value-free audit → .watchlight/audit.jsonl
                                 ▼
                 watchlight dev  ·  http://localhost:7000

  Production = the SAME code, pointed at the governed control plane
  (signed audit · multi-tenant · drift→quarantine · fleet revocation).

Just want everything? pip install "watchlight[all]" pulls the SDK, all framework plugins, and the MCP PEP in one go — so every example on docs.watchlight.ai/de runs with a single install. Note the SDK's module name is watchlight_core (there is no watchlight-core package on PyPI).

Runnable, self-contained examples for every one of these are in examples/ — start with examples/governed_research_agent.py.

Quickstart

The govern decorator, watchlight dev, and the framework + MCP integrations below all work today. Full guide: Developer Edition docs.

Prerequisites: Python 3.9+. Prebuilt wheels ship for Linux, macOS, and Windows — no Rust toolchain, no build step, no account.

pip install watchlight

Prefer an isolated environment? Install into a virtual environment instead:

python -m venv .venv
source .venv/bin/activate        # Windows: .venv\Scripts\activate
pip install watchlight

Save this as agent.py and run python agent.py:

# agent.py — a complete, runnable program (copy, paste, run).
from watchlight import govern, Denied

# Permit ONLY the "research" intent. Fail-closed: everything else is denied.
govern.allow('permit(principal, action == Action::"research", resource);')

@govern.tool(intent="research")
def web_search(query: str) -> str:
    return f"results for: {query}"

@govern.tool(intent="transfer")           # governed, but no policy permits it
def transfer_funds(to: str, amount: int) -> str:
    return f"sent ${amount} to {to}"      # never runs — denied first

print(web_search("watchlight docs"))      # ALLOW → the body runs
try:
    transfer_funds("mallory", 1000)       # DENY → refused before the body runs
except Denied as e:
    print(e)

$ python agent.py
watchlight: governing 'my-agent' (dev mode, in-process engine)
watchlight: ALLOW  research  tool/web_search
results for: watchlight docs
watchlight: DENY   transfer  tool/transfer_funds     not authorized
watchlight denied intent 'transfer' on tool/transfer_funds: not authorized

That DENY line — in your own terminal, in under five minutes, with no account — is the product. The transfer_funds body never ran.

TypeScript / Node

Same governance, in your Node app — no Python sidecar. @watchlight/sdk runs the same compiled engine in-process (WebAssembly).

Prerequisites: Node ≥ 18. @watchlight/sdk pulls in the compiled engine (@watchlight/engine) automatically — no native toolchain.

npm install @watchlight/sdk

Then, in an ES-module / TypeScript file (await at top level needs "type": "module" or a .mjs file):

// agent.ts — the same DENY line, in Node.
import { govern, Denied } from "@watchlight/sdk";

// Permit ONLY the "research" intent. Fail-closed: everything else is denied.
govern.allow('permit(principal, action == Action::"research", resource);');

async function webSearch(query: string) { return `results for: ${query}`; }
async function transferFunds(to: string, amount: number) { return `sent $${amount} to ${to}`; } // never runs

const search   = govern.tool(webSearch,     { intent: "research" });
const transfer = govern.tool(transferFunds, { intent: "transfer" });   // no policy permits it

console.log(await search("watchlight docs"));   // ALLOW → the body runs
try {
  await transfer("mallory", 1000);              // DENY → refused before the body runs
} catch (e) {
  if (e instanceof Denied) console.log(e.message);
}

watchlight: governing 'my-agent' (dev mode, in-process engine)
watchlight: ALLOW  research  tool/webSearch
results for: watchlight docs
watchlight: DENY   transfer  tool/transferFunds     not authorized
watchlight denied intent 'transfer' on tool/transferFunds: not authorized

It mirrors the Python package feature-for-feature:

• Runtime context, per-user, human-in-the-loop: govern.tool(fn, { intent, principal?, resource?, context?, onNeedsApproval?, onResult? }) — runtime facts into Cedar context.*, per-call principal, and a three-state Allow / Deny / NeedsApproval verdict with a single-use approval token.
• Govern what a tool returns: onResult(result, { intent, resource, principal, decisionId, obligations? }) (Python on_result) runs after the body and before the caller sees the result — sanitize, screen, honour the decision's obligations, or re-authorize on its classification; a returned value replaces the payload, a throw withholds it (fail-closed). Writes a value-free egress audit record joined to the decision by decision_id.
• Obligations on an Allow: a permit annotated @obligate_redact("ssn"), @obligate_max_items("25"), @obligate_log_values("false") (or any @obligate_<name>("raw")) yields d.obligations — { redact, maxItems, logValues, extra } (Python result["obligations"]: redact / max_items / log_values / extra, the last as {name: [values]}) — constraints your code or onResult must honour. Several carriers merge to the strictest reading; only an Allow carries them; Deny and NeedsApproval never do; an unreadable obligation fails closed (AuthorizeError). Needs engine >= 0.2.0. See the allow-but-redact pattern.
• Frameworks: governedHooks() for the Claude Agent SDK; governTool() for LangChain / LangGraph.js.
• Data minimization: govern.sanitize(text, { resource, decisionId, known? }) — strip PII before an agent reads a document: structured detectors (email, phone, SSN, card, IBAN, IPv4, API key, labelled passport / date of birth), an app-supplied known dictionary (KNOWN; simple case-insensitive match — Unicode case folding differs between lanes), and opt-in PERSON / ADDRESS heuristics. Pass the decisionId from authorize and the sanitization audit line joins the decision on decision_id.
• Content screening: govern.screen(text, { resource, decisionId? }) — flag or redact prompt-injection shapes in what a read returns, before it reaches the model; with the decisionId the screening audit line joins the decision.
• Attenuation & graduation: govern.scope().attenuate(); scope.toToken() / govern.scopeFromToken() carry an attenuated scope to a worker process (HMAC integrity; the receiving engine re-proves the subset); every decision returns a decisionId to join to your records; WATCHLIGHT_APDP_URL graduates the same code to the control plane.

Full API + runnable examples: ts/ · npm: @watchlight/sdk (glue, Apache-2.0) + @watchlight/engine (the compiled engine). Docs: docs.watchlight.ai/de/typescript.

Already using a framework? Govern it in-process

Bring your existing LangGraph, Pydantic AI, or Claude Agent SDK agent under governance with zero infrastructure — the same plugin you ship to production, wired to the in-process engine:

pip install 'watchlight[langgraph]'   # or [pydantic-ai], [claude-agent]

from watchlight.langgraph import governed_plugin   # .pydantic_ai / .claude_agent

plugin = governed_plugin("watchlight.policy.json")   # in-process, zero infra

async with await plugin.start_run("research-agent") as handle:
    if not await handle.authorize_action("read", "tool/web_search"):
        raise PermissionError("denied before it executed")
    ...  # your tool runs, every action governed + recorded to .watchlight/audit.jsonl

Going to production is one environment variable, not a rewrite — set WATCHLIGHT_APDP_URL and the identical code authorizes against a running policy service. Runnable examples for all three frameworks are in examples/.

Watch every decision live — watchlight dev

A zero-dependency local dashboard that tails your value-free audit trail and shows every governance decision as it happens — the ALLOWs, and the DENYs that stopped a tool before it ran.

watchlight dev            # → http://127.0.0.1:7000

Run your governed agent in another terminal and watch the decisions stream in. It shows only this process — fleet-wide lineage, signed audit, and drift→quarantine are the governed control plane (Enterprise).

On an ephemeral host, keep the trail: pass an audit_sink and every record — decisions, sanitizations, attenuations — is also handed to your code with exactly the fields the file line carries (the file stays on). The sink is fire-and-forget and can never block or change a decision; a failure is reported once.

govern = Watchlight(agent="my-agent", audit_sink=lambda record: my_store.insert(record))

Reference sinks — a Postgres row, an OTLP log record, a webhook — are in examples/patterns/audit-sink.md.

The trail is also an input: govern.counters(...) folds it into a number for a quota policy — decisions for exactly this principal (and intent / resource) in the last window, from the record timestamps — so context.reads_this_hour < 100 has something to compare against. Streams the local file (bounded, 64 MiB by default); malformed lines are skipped and counted, never echoed.

c = govern.counters(principal='User::"u1"', intent="read", window="1h")   # {"count": 7, "window": {...}, ...}
govern.authorize(action="read", principal='User::"u1"', context={"reads_this_hour": c["count"]})

The quotas pattern has the policy, the tool binding, and the exact counting rules.

Test your policies before they gate real actions

A policy is the only thing standing between an agent and a real action, so unit-test it like any other code. Golden fixtures assert the expected verdict (Allow / Deny / NeedsApproval) for a (principal, action, resource, context); a wrong expectation fails the suite. Run it in CI.

from watchlight import govern

govern.load("watchlight.policy.json")
report = govern.test([
    {"name": "under limit allows", "action": "book",
     "context": {"amount": 200, "limit": 500, "refundable": True}, "expect": "Allow"},
    {"name": "over limit denies", "action": "book",
     "context": {"amount": 800, "limit": 500, "refundable": True}, "expect": "Deny"},
    {"name": "big wire needs a human", "action": "wire",
     "context": {"amount": 5000}, "expect": "NeedsApproval"},
])
assert report["failed"] == 0, report

govern.test(...) (Node: await govern.test([...])) drives the engine's decision core directly, so it never writes the audit trail and holds zero decision logic — every verdict is the engine's. Set "approved": true on a fixture to mint a single-use token and assert the human-confirmed NeedsApproval → Allow downgrade; set "obligations": {"redact": ["ssn"]} to also assert the obligations an Allow carries (exact match; {} asserts none).

Or from CI, with the CLI — a suite.json of { policyFile?, policies?, tests: [...] }, exit 1 on any failure:

watchlight policy test suite.json          # Python
npx watchlight policy test suite.json      # Node

Patterns — advanced policies for high-stakes decisions

Past the quickstart, the interesting question is what to write in the policy. The governance patterns library is a set of copy-paste recipes for the decisions people reach for the Developer Edition to govern — spending money, deleting things, messaging the outside world, moving data, killing a runaway agent. Each is a problem shape: a policy, the code that governs the tool, and tests that prove the verdicts. Every policy is run through the real engine by check.sh, so what a pattern claims and what the engine does can't drift.

The advanced policy JSON — each a runnable { policies, tests } suite with Cedar context conditions and @enforcement_effect gates — lives under examples/patterns/suites/:

Patterns whose guarantee is not a policy verdict — sanitization, content screening, scope attenuation, the audit sink — are verified by a Node script under examples/patterns/scripts/ instead. Run every suite and script at once:

examples/patterns/check.sh          # every pattern must have a suite or script; runs them all

Govern an MCP server

Put a policy enforcement point (PEP) in front of any MCP server (spec 2026-07-28). The MCP PEP authorizes every governed call — tools/call, resources/read, resources/subscribe, prompts/get — in-process before it reaches the server, so a denied call never executes.

pip install watchlight-mcp

import watchlight_mcp

watchlight_mcp.serve(
    listen_addr="127.0.0.1:9700",
    upstream_url="http://localhost:3000/mcp",   # the MCP server you're governing
    upstream_server="github",
    policy_files=["examples/mcp.policy.json"],
    audit_path=".watchlight/audit.jsonl",       # ← the file `watchlight dev` tails
)

Point your MCP client at http://127.0.0.1:9700/mcp instead of the server. A self-contained, self-demonstrating example (it fires an allowed and a denied call and proves the denied one never ran) is in examples/governed_mcp_server.py.

For a stdio-launched server use serve_stdio(...); to run non-blocking and hot-reload policies use serve_background(...). Pass tls_cert=/tls_key= to terminate HTTPS on the listener, and upstream_ca= to trust a private https:// upstream. See the MCP server guide.

Watch the MCP decisions live

watchlight dev tails .watchlight/audit.jsonl — so give the PEP the same audit_path (above) and run the console beside it, from the same directory:

# terminal 1 — the governed MCP server, auditing to the file the console tails
python examples/governed_mcp_server.py

# terminal 2 — the live console
watchlight dev                # → http://127.0.0.1:7000

Every tools/call decision streams in — the tool, the upstream it fronts, and the reason a call was denied. (The example prints the exact watchlight dev --audit … command for its own audit file.)

What runs locally

Everything the Developer Edition removes is infrastructure, never a guarantee. Fail-closed semantics, engine-side attenuation, explicit scopes, and value-free audit are identical in every mode.

Open source, and the compiled engine

Everything you write against is open and Apache-2.0 — read it, audit it, fork it:

• watchlight — the govern decorator, govern.scope attenuation, the CLI, and the watchlight dev dashboard
• the framework plugins — watchlight-langgraph, watchlight-pydantic-ai, watchlight-claude-agent
• the MCP PEP's transport layer, and every example in this repo

The decision engine ships as a compiled wheel — watchlight-engine (the Cedar authorization pipeline) and the watchlight-mcp runtime — both free to use, including in production and commercially — for up to 25 governed agents per organization (a commercial license is needed only above that, or to re-offer the engine itself as a hosted authorization service). The engine source is the part Watchlight sells; the code you integrate with is not.

You don't have to trust a black box to trust the decisions:

• The policy language is open. Decisions are standard Cedar — an open, formally-specified language; the same policy yields the same decision, deterministically.
• The integration layer is open. The SDK, plugins, CLI, and PEP transport are all readable here, so you can see exactly what the engine is asked and what it returns.
• Every decision is on disk. Each ALLOW/DENY is appended, value-free, to .watchlight/audit.jsonl — inspect the engine's behaviour on your own machine, tool by tool.

Want the engine source or an air-gapped build? That's Enterprise — email sales@watchlight.ai.

A note on identity

The Developer Edition authorizes the principal you assert — the agent you construct the governor with, or the Watchlight-Agent-Id a governed MCP request carries. It does not cryptographically prove the caller: on your own machine, running both sides, that's the right trade — zero setup, no IdP, no signup. Bind any non-loopback listener behind something that authenticates the caller (a reverse proxy doing mTLS/OIDC, or the Enterprise plane).

Identity hardens as you grow, without changing your policies:

• Developer Edition — the principal is asserted (cooperative, local-dev).
• Next — an optional signed session token binds the principal to a key your process holds, so a prompt-injected sub-agent can't rewrite a header to escalate — still no external infrastructure.
• Enterprise — identity is attested: federated (OIDC) and workload (mTLS) identity, cryptographically verified across the fleet.

Only how strongly the principal is proven changes between these — the policies you write do not.

Developer Edition vs Enterprise

The Developer Edition is the real engine, free and in-process; Enterprise points the same code — no rewrite — at the governed control plane, adding signed tamper-evident lineage, multi-tenant isolation, drift→quarantine, and fleet-wide revocation across every agent and environment.

→ watchlight.ai

License

The Developer-Edition SDK, the framework plugins, this repository, and the watchlight dev dashboard are Apache-2.0 — use, fork, and ship them freely. The authorization engine (watchlight-engine) and the MCP runtime (watchlight-mcp) ship as compiled wheels under the Watchlight Developer Edition license; they are free to use, including in production and commercially, for up to 25 governed agents per organization — a commercial license is needed only above that, or to re-offer the engine itself as a hosted authorization service.

Want the engine source, an air-gapped build, or to govern a fleet in production? That's the Enterprise plane — email sales@watchlight.ai.