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ExecGate is a verification boundary between AI-generated plans and trusted Python code.

It validates proposed actions against registered capabilities, schemas, policies, references, and live application state before normal handler execution.

from execgate import Logix

logix = Logix()


@logix.capability
def add(a: int, b: int) -> int:
    """Add two integers."""
    return a + b


result = logix.run({
    "call": "add",
    "with": {"a": 10, "b": 20},
})

if result.ok:
    print(result.value)  # 30
else:
    print(result.errors)

ExecGate infers schemas from type annotations, extracts descriptions from docstrings, and registers capabilities. Your handlers remain ordinary Python functions.

ExecGate does not decide what your application should permit. It enforces the rules you define.

Why ExecGate?

AI applications increasingly let models select tools, generate structured arguments, and propose actions. Your application still needs to verify that those proposals are valid and authorized.

ExecGate provides a boundary for checks such as:

• Capability validation — reject unknown or invented capability names.
• Schema validation — validate arguments and enforce declared types.
• Reference validation — reject malformed plans and invalid dependencies.
• Policy enforcement — check configured rules before execution.
• Live-state authorization — evaluate application state when an action is verified and executed.
• Human approval — add approval gates for sensitive operations.
• Idempotency — help prevent duplicate execution when retries occur.
• Failure handling — distinguish verification rejection from execution failure.

Explore the System Design and Security Model.

Installation

pip install execgate

Optional integrations:

pip install "execgate[pydantic]"  # Pydantic model support
pip install "execgate[ai]"        # AI provider adapters
pip install "execgate[mcp]"       # MCP server and proxy
pip install "execgate[all]"       # All configured extras

Requirements: Python 3.11 or later.

The core package has zero third-party runtime dependencies. Optional integrations extend the core without making Pydantic, FastMCP, or provider SDKs mandatory for import execgate.

Three ways to use ExecGate

1. Use it as a dispatcher

You don't need an AI model to benefit from schema-checked capability execution.

result = logix.run({
    "call": "add",
    "with": {"a": 1, "b": 2},
})

This can be useful in scripts, tests, command-line tools, and webhook handlers.

2. Connect an AI model

Let a model propose a plan, then pass that proposal through ExecGate's verification pipeline.

catalog = logix.tools.format("openai")
plan = adapter.parse_proposal(ai_response)

result = logix.run(plan, context=ctx)

The AI proposes. ExecGate verifies. Your handler executes only if the required checks pass.

3. Separate verification from execution

For workflows that need explicit approval or additional control, verify first and execute afterward.

report = logix.verify(plan, context=ctx)

approval = ask_human(report.verified_plan)

result = logix.execute(
    report.verified_plan,
    context=ctx,
    approval=approval,
)

This separation lets you introduce approval gates, live-state invariants, and bounded retries into your application workflow.

Start with the Getting Started Guide or follow Lesson 01: Refund Workflow.

Works with any AI that emits JSON

ExecGate's core is provider-neutral. It can process plans from hosted models, local models, scripts, or other sources.

catalog = logix.tools.format("json")    # Provider-neutral format
catalog = logix.tools.format("openai")  # Optional provider format

Provider adapters are optional translators, not a requirement. A plan from an AI provider and a plan written by hand go through the same verification pipeline.

See AI Integration.

MCP integration

ExecGate supports both MCP server and proxy workflows through the optional execgate_mcp package.

Server mode

Expose registered ExecGate capabilities to an MCP client.

from execgate_mcp import LogixMCPServer

server = LogixMCPServer(logix, name="order-service")
server.run()

The example uses stdio transport. Calls are routed through logix.run().

Proxy mode

Verify calls to an upstream MCP server before forwarding them.

from execgate_mcp import LogixMCPProxy

proxy = LogixMCPProxy(logix, "http://upstream/mcp")

await proxy.startup()

try:
    await proxy.run_async()
finally:
    await proxy.shutdown()

The execgate_mcp package follows the leaf-node architecture described in ADR-0007. It imports the public Logix API and shared types rather than reaching into the verifier, executor, or intermediate representation.

Limitation: MCP approval workflows have documented restrictions. Review the MCP Guide before designing an approval-dependent MCP deployment.

How verification works

AI / script / MCP client
          |
          | Untrusted proposal
          v
+--------------------------------------+
|               ExecGate               |
|                                      |
|  Parse -> Ground -> Verify           |
|                    |                 |
|                    v                 |
|              VerifiedPlan            |
|                    |                 |
|                    v                 |
|  Recheck invariants, approval,       |
|  and idempotency during execution    |
+--------------------|-----------------+
                     |
                     v
            Trusted handlers
          (database, payments, etc.)

The executor accepts a VerifiedPlan, not an arbitrary dictionary claiming to be verified. Dynamic checks are re-evaluated during execution immediately before the handler runs.

Verification is not the same as authorization. ExecGate can enforce the rules and checks implemented by your application, but it cannot invent missing business rules or guarantee that every permitted action is harmless.

Read the System Design and Security guides for the detailed model.

What's included?

Package	Purpose	Runtime dependencies
logiq	Registry, schema engine, verifier, executor, semantic layer	Python standard library
execgate_pydantic	Pydantic models as capability schemas	pydantic>=2,<3
execgate_ai	Provider-catalog adapters	None
execgate_mcp	MCP server and proxy	fastmcp>=4,<5

Optional packages are not required to use the core dispatcher. The core's zero-dependency guarantee is also checked by the project's import-boundary tests.

Documentation

The ExecGate documentation site contains guides, API references, architecture decisions, and security documentation.

Guide	What you'll learn
Getting Started	Build your first capability and plan
Usage Model	Understand the developer, AI, and verification boundary
System Design	Follow the execution pipeline and failure model
API Reference	Explore the public API
Security	Understand the threat model and security tests
Semantic Layer	Learn about grounding, invariants, approval, and idempotency
Plan Format	Understand plan structure, $ref, and versioning
Schemas	Learn about schema inference and strict types
AI Integration	Connect AI providers to ExecGate
Writing an Adapter	Build a provider adapter
MCP	Configure server and proxy modes
Production Guide	Review deployment, observability, and incident response

The documentation source is available in docs/. Architecture decision records are in docs/adr/.

Examples

The repository includes standalone scripts in examples/.

Example	Demonstrates
01_quickstart.py	Register a capability and run a plan
02_ai_tool_catalog.py	Describe and format tool catalogs
03_multistep_refs.py	Multi-step plans, $ref, and grounding
04_refund_with_approval.py	Verify, request approval, and execute
05_pydantic_models.py	Use Pydantic models as schemas
06_fastapi_worker.py	Embed ExecGate in a FastAPI worker
07_local_model_ollama.py	Use a local model with JSON-mode prompting
08_write_your_own_adapter.py	Write a custom provider adapter
09_mcp_server_quickstart.py	Expose capabilities to MCP clients
10_mcp_proxy_refund.py	Verify calls before forwarding upstream
11_mcp_approval_elicitation.py	Explore approval in MCP deployments
12_xerj_native.py	Use XERJ search as a native capability

Run the basic quick start with:

python examples/01_quickstart.py

Check each example's imports and requirements before running it; optional integrations may need their corresponding extras installed.

Project status

Version: 0.1.0 · Status: Alpha · Active development

Implemented

• The core pipeline: parsing, grounding, verification, execution-time rechecks, and output validation.
• Semantic-layer features for grounding, invariants, approval, idempotency, and bounded repair.
• Optional Pydantic, AI-provider, and MCP integrations.
• Security tests covering documented verification guarantees.
• Getting-started guides, lessons, API documentation, and architecture decision records.

Known limitations and future work

• logix.dry_run() and logix.explain() are reserved names; their behavior is deferred.
• The default idempotency store is in-memory. Applications needing durable idempotency must implement the IdempotencyStore protocol using their own storage.
• Plan execution is sequential in version 0.1.0.
• MCP approval workflows have documented limitations.

ExecGate is not yet production-ready. Review the Production Guide and MCP limitations before deployment.

Security

ExecGate is security-adjacent software. Its verification boundary can enforce implemented checks, but it does not guarantee that handlers are correct, that business rules are complete, or that permitted actions are safe.

Please do not report security vulnerabilities through public GitHub issues. Follow the private disclosure process described in CONTRIBUTING.md.

For the threat model, limitations, and guarantee-to-test mapping, see the Security Guide.

Contributing

Contributions are welcome. Start with CONTRIBUTING.md.

git clone https://github.com/aldanedev-create/ExecGate.git
cd ExecGate
pip install -e ".[dev]"
pytest
python scripts/preflight.py

Key project constraints include:

• The core test suite must pass without Pydantic or FastMCP installed.
• scripts/check_imports.py checks the zero-dependency import boundary.
• tests/mcp/test_leaf_node_boundary.py checks the MCP adapter's architectural boundary.

Run the documented checks before submitting changes.

License

ExecGate is licensed under the MIT License. See LICENSE.

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