Titmas Agent Action Gate
FreeNot checkedAn MCP server that enforces deterministic authorization boundaries for AgentTeams workflows by verifying evidence and policy, returning ALLOW, BLOCK, or REQUIRE
About
An MCP server that enforces deterministic authorization boundaries for AgentTeams workflows by verifying evidence and policy, returning ALLOW, BLOCK, or REQUIRE_APPROVAL decisions before actions are executed.
README
Evidence-verified, deterministic authorization boundaries for AgentTeams workflows.
中文:面向 AgentTeams 多智能体工作流的证据验证与确定性行动闸门。
TITMAS Agent Action Gate is a production-oriented reference architecture and competition demo candidate for the GOAI 2026 Agent Infra track. It separates uncertain agent analysis from deterministic authorization, evidence verification, policy evaluation, and human approval.
Current milestone: M4_RUNTIME_BLOCKER_CLOSURE_IN_PROGRESS; the bounded Alibaba Cloud official Skill sub-milestone is COMPLETE, while full M4 remains INCOMPLETE.
The deterministic Action Gate, append-only state store, pinned agent-evidence adapter, authenticated native MCP boundary, six-role target topology, and allowlisted in-memory GitHub provider adapter are implemented in the current worktree. A bounded public sandbox run previously created a branch and Draft PR. On 2026-08-02, a historical isolated deployment of official AgentTeams v1.2.0 started one Manager and five Workers; it remains operator-supervised negative evidence. A separate disposable cloud-context-inspector ran one native Qwen Worker turn: it resolved the externally installed official Alibaba Cloud Resource Center Skill, verified the source-lock digest, invoked the frozen typed read-only adapter, and returned EMPTY_RESULT as NOT_ASSESSED_NO_VISIBLE_RESOURCE. The retained chains and canonical agent-evidence receipt validate, while Worker decision records and Resource Center write calls remain zero. This proves only the bounded specialist turn, not a complete cloud inventory, broader autonomous M4 completion, or deployment authorization.
This repository is not submitted to, endorsed by, or affiliated with GOAI, and it makes no certification, compliance, production-readiness, or security guarantee.
Why this exists
Agents are useful at interpreting ambiguous requests, decomposing work, and explaining uncertainty. They should not be the component that silently grants their own authority. This project uses:
- AgentTeams v1.2.0 for transparent Manager/Leader/Worker collaboration;
- agent-evidence 0.6.0 as the canonical evidence packaging and verification dependency;
- versioned JSON contracts and a deterministic Action Gate for
ALLOW,BLOCK, andREQUIRE_APPROVAL; - a human approval record for scoped, high-risk actions;
- provider MCP servers, such as GitHub MCP, only after an
ALLOWdecision.
AgentTeams team
| AgentTeams Worker | Responsibility | Cannot do |
|---|---|---|
workflow-lead |
Route tasks and preserve handoffs | Decide authorization or execute GitHub writes |
request-analyst |
Normalize requests, risk signals, and uncertainty | Grant permission or validate its own output |
evidence-verifier |
Invoke the pinned agent-evidence verifier and return its receipt |
Rewrite evidence or decide policy |
github-operator |
Execute an exact GitHub action after a matching ALLOW |
Bypass the gate or approve releases |
cloud-context-inspector |
Request one typed, current-account Resource Center search and return sanitized context | Receive credential bytes, run arbitrary CLI/cloud operations, write cloud state, or decide the gate |
release-steward |
Assemble post-execution evidence and request the release decision | Merge, tag, or release without a new decision |
Agent identities and intended tool boundaries are machine-readable in agents/registry.json. The reviewable deployment template is deploy/agentteams/team.v1.2.0.yaml; the non-idempotent macOS Docker Desktop smoke profile is deploy/agentteams/team.native-smoke.v1.2.0.yaml.
Native local smoke boundary
The retained machine-readable evidence is demo/evidence/agentteams-native-20260802.json. It records both the verified chain and the failures that prevent a stronger claim:
- Qwen
qwen3.8-max-previewspecialist Workers invoked the real six-tool MCP endpoint; preview model availability is not a stable runtime contract; agent-evidence0.6.0returnedVALID, after which the deterministic gate returned a five-minuteALLOWthat expired without execution;- the leader did not complete the workflow autonomously, one unrelated request entered the global store during concurrent prompts, and
github-operatorcalled a tool outside its declared registry allowlist; - all Workers shared the same MCP endpoint, so prompts described role boundaries but the smoke did not enforce per-Worker tool ACLs;
- repository Skill names were declared in resources, but the run did not independently prove that those Skill packages were materialized inside the Workers.
This is native local orchestration evidence, not a persistent deployment, autonomous-workflow proof, least-privilege proof, or production-readiness evidence.
Deterministic decisions
| Outcome | Meaning |
|---|---|
ALLOW |
The exact action, target, evidence, policy, and any required approval match. Execution may be attempted; success is not implied. |
BLOCK |
The request is malformed, denied, unsupported, missing required evidence, or has invalid/tampered evidence or approval. |
REQUIRE_APPROVAL |
Evidence and policy inputs are otherwise valid, but the risk class requires a scoped human approval before re-evaluation. |
The decision contract and precedence rules are in specs/action-gate-decision-v0.1.md.
GitHub demo path
Agent request
-> request analysis
-> pre-action evidence verification
-> deterministic Action Gate
-> exact GitHub action after ALLOW
-> official Alibaba Cloud read-only context preflight before a deployment-related release request is evaluated
-> post-action evidence generation
-> agent-evidence verification
-> deterministic release decision
-> human approval when required
The end-to-end scenario and retained public evidence are documented in docs/GITHUB-WORKFLOW-DEMO.md. The repository contains four reproducible runtime cases: valid execution, missing evidence, tampered evidence, and a high-risk release action requiring approval.
The historical adapter-only Alibaba Cloud evidence is demo/evidence/alibabacloud-resourcecenter-preflight-20260802.json. The later native Worker-turn evidence is demo/evidence/agentteams-native-alibabacloud-skill-20260802.json. The frozen four-file evidence set is demo/evidence/alibabacloud-evidence-set-freeze-20260802.json. Together they retain exact external Skill source verification, pinned CLI/plugin digests, same-profile live STS identity binding, the complete one-policy RAM attachment set, sanitized invocation trace, CLI exit 0, native AgentTeams Worker and Matrix receipts, replayable VALID agent-evidence, and scoped zero-write accounting. The Worker ZIP contains reference metadata but no upstream Skill bytes.
Run and validate
Python 3.11 or newer is required.
python3 -m pip install -e '.[dev]'
python3 scripts/validate_milestone.py
python3 scripts/validate_governance.py
python3 scripts/validate_alibabacloud_runtime_evidence.py
python3 scripts/validate_alibabacloud_evidence_set.py
python3 scripts/validate_native_agentteams_cloud_skill_evidence.py \
demo/evidence/agentteams-native-alibabacloud-skill-20260802.json
python3 -m unittest discover -s tests -v
python3 -m titmas_action_gate.cli evaluate-fixtures
python3 -m titmas_action_gate.cli demo --state-dir artifacts/runtime/local-demo
python3 -m titmas_action_gate.cli validate-install
Run a future real Alibaba Cloud preflight only through the runner's internal same-run RAM readback. It generates an unpredictable run ID and atomically reserves the evidence path before any provider call. It does not accept an external observation or credential bytes:
python3 scripts/run_alibabacloud_skill_evaluation.py \
--control-profile '<RAM-readback-profile-label>' \
--profile '<read-only-profile-label>' \
--role-name '<read-only-role-label>' \
--output '<new-evidence-path>' \
--confirmation-ref '<explicit-user-confirmation-reference>'
The tests execute the deterministic engine, pinned agent-evidence validator, append-only chain, MCP stdio protocol, all six tools, AgentTeams-compatible local handoffs, in-memory provider workflow, native-smoke manifest/evidence checks, and negative boundaries. They do not prove persistent AgentTeams deployment, autonomous orchestration, production security, or operational readiness.
Start the MCP server over stdio:
TITMAS_ACTION_GATE_STATE_DIR='artifacts/runtime/mcp' \
TITMAS_ACTION_GATE_CALLER_TOKEN='replace-with-agent-token' \
TITMAS_ACTION_GATE_APPROVER_TOKEN='replace-with-distinct-approver-token' \
TITMAS_ACTION_GATE_DEMO_MODE='true' \
TITMAS_ACTION_GATE_MCP_TRANSPORT='stdio' \
titmas-action-gate-mcp
The real GitHub runner requires a separately provisioned sandbox repository and exact local worktree. It is intentionally not part of default CI. See docs/RUNBOOK.md.
Repository map
- architecture/README.md: system boundaries and data flow;
- docs/AGENTTEAMS-INTEGRATION-PLAN.md: AgentTeams v1.2.0 integration;
- docs/SKILL-SPECIFICATION-v0.1.md: reusable Skill package contract;
- docs/MCP-TOOL-SPECIFICATION-v0.1.md: MCP server and tool contract;
- docs/THREAT-MODEL-v0.1.md: trust boundaries and bypass threats;
- docs/ALIBABA-CLOUD-SKILL-INTEGRATION.md: exact official Skill source, typed read-only boundary, credential isolation, evidence path, and current exit status;
- docs/EXECUTION-ROADMAP.md: implementation and evaluation gates;
- docs/RUNBOOK.md: reproducible local and sandbox commands;
- SECURITY.md: security model, reporting, and non-production limitations;
- evaluations/: deterministic contract cases;
- governance/: DBA source lock, existence declaration, recommendation, and management boundary.
Truth boundaries
AGENTTEAMS_ORCHESTRATION_NE_ACTION_AUTHORITY=true
AGENT_ANALYSIS_NE_POLICY_DECISION=true
EVIDENCE_NE_TRUTH=true
EVIDENCE_VERIFICATION_NE_ACTION_AUTHORIZATION=true
ALLOW_NE_EXECUTION_SUCCESS=true
MCP_TOOL_AVAILABILITY_NE_PERMISSION=true
SPECIFICATION_NE_IMPLEMENTATION=true
TEST_PASS_NE_PRODUCTION_READINESS=true
LOCAL_HANDOFF_HARNESS_NE_NATIVE_AGENTTEAMS_RUNTIME=true
NATIVE_LOCAL_SMOKE_NE_PERSISTENT_OR_PRODUCTION_DEPLOYMENT=true
OPERATOR_SUPERVISED_NE_AUTONOMOUS_END_TO_END=true
HASH_CHAIN_VALID_NE_SEMANTIC_ORCHESTRATION_CLEAN=true
PROMPT_ROLE_BOUNDARY_NE_ENFORCED_PER_WORKER_ACL=true
CLOUD_CONTEXT_NE_DEPLOYMENT_AUTHORIZATION=true
CLOUD_READ_SUCCESS_NE_COMPLETE_INVENTORY_OR_READ_ONLY_POLICY_PROOF=true
GITHUB_PR_CREATED_NE_GITHUB_PR_MERGED=true
COMPETITION_REPOSITORY_NE_COMPETITION_SUBMISSION=true
TITMAS_CORE_PROTOCOLS_CHANGED=false
License
Original project code is Apache-2.0. See LICENSE.
The externally installed third-party alibabacloud-resourcecenter-search subtree has SPDX-License-Identifier: NOASSERTION in this repository's source lock because upstream has no applicable license file and its README contains conflicting Apache-2.0 and MIT statements. Installation and byte provenance do not establish redistribution, derivative-work, commercial-use, or compatibility clearance. The subtree is absent from the repository, Worker packages, wheel, and sdist; it must not be included in a public commit or release. See governance/alibabacloud-resourcecenter-search-source-lock.json.
Installing Titmas Agent Action Gate
This server has no published package — it is built from source. Open the repository and follow its README.
▸ github.com/joy7758/titmas-agent-action-gateFAQ
Is Titmas Agent Action Gate MCP free?
Yes, Titmas Agent Action Gate MCP is free — one-click install via Unyly at no cost.
Does Titmas Agent Action Gate need an API key?
No, Titmas Agent Action Gate runs without API keys or environment variables.
Is Titmas Agent Action Gate hosted or self-hosted?
Self-hosted: the server runs locally on your machine via the install command above.
How do I install Titmas Agent Action Gate in Claude Desktop, Claude Code or Cursor?
Open Titmas Agent Action Gate on unyly.org, pick your client tab (Claude Desktop, Claude Code, Cursor) and press Install — the config is generated automatically, no JSON editing.
Related MCPs
Fetch
Web content fetching and conversion for efficient LLM usage.
AWS KB Retrieval
Retrieval from AWS Knowledge Base using Bedrock Agent Runtime.
by modelcontextprotocolSpring AI MCP Server
Provides auto-configuration for setting up an MCP server in Spring Boot applications.
llm-analysis-assistant
A very streamlined mcp client that supports calling and monitoring stdio/sse/streamableHttp, and can also view request responses through the /logs page. It also
by xuzexin-hzCompare Titmas Agent Action Gate with
Not sure what to pick?
Find your stack in 60 seconds
Author?
Embed badge for your README
Browse similar
All ai MCPs
