Jott2121/agent-gate
by Various
MCP server that adds a fail-closed quality gate and hash-chained receipt ledger to any AI agent workflow.
MCP
Jott2121/agent-gate
Added 11 June 2026
Overview
Agent-gate is an MCP server that enforces a fail-closed quality gate on AI agent outputs and maintains a hash-chained receipt ledger for auditability. It integrates into existing MCP-compatible agent workflows to block low-quality responses and create an immutable log of decisions.
Best for
Best for
Developers deploying MCP-based AI agents that need output quality control and an immutable audit trail
Use cases
- Blocking agent outputs that fail a predefined quality threshold
- Generating tamper-proof receipts for each agent action
- Integrating quality control and auditing into MCP-based agent pipelines
Notes
Agent-gate is an MCP server that enforces a fail-closed quality gate on AI agent outputs and maintains a hash-chained receipt ledger for auditability. It integrates into existing MCP-compatible agent workflows to block low-quality responses and create an immutable log of decisions.
1 stars on GitHub. Last updated 2026-06-11. Licensed MIT.
Use cases
- Blocking agent outputs that fail a predefined quality threshold
- Generating tamper-proof receipts for each agent action
- Integrating quality control and auditing into MCP-based agent pipelines
Pros
- Fail-closed gate prevents low-quality or unsafe outputs from reaching users
- Hash-chained ledger provides a verifiable, immutable audit trail
- Lightweight Python server that is easy to deploy and integrate
Cons
- Early-stage project with limited community and documentation
- Adds latency to agent workflows due to quality checks and ledger writes
- Requires a compatible MCP agent framework to function
Indexed from awesome-mcp-servers-punkpeye and enriched against its public facts.
Pros
- Fail-closed gate prevents low-quality or unsafe outputs from reaching users
- Hash-chained ledger provides a verifiable, immutable audit trail
- Lightweight Python server that is easy to deploy and integrate
Cons
- Early-stage project with limited community and documentation
- Adds latency to agent workflows due to quality checks and ledger writes
- Requires a compatible MCP agent framework to function
Pairs with
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