IAM Policy Autopilot is an open source static code analysis tool that helps you quickly create baseline AWS IAM policies that you can refine as your application evolves. This tool is available as a command-line utility and MCP server for use within AI coding assistants for quickly building IAM policies.

Enables agents to validate enterprise travel policies, audit hotel rate parity, and check carbon ESG compliance through a zero-dependency MCP server. It exposes policy and expense-auditing tools over STDIO JSON-RPC for use in Claude Desktop, Cursor, or other MCP runtimes.

Australian lender credit policy library and client files for mortgage and finance brokers.

An MCP proxy that sits in front of bank tool servers, letting AI agents make read-only calls like balances and transactions while blocking payments, writes, renamed tools and argument smuggling. Each denial produces an Ed25519-signed receipt that can be verified offline.

Enables automated validation of corporate travel policies, hotel rate-parity audits, and carbon ESG compliance checks through MCP tools.

Audit trail and traceability for AI agents. See what every coding agent did, block risky calls, ask a human for approval, and prove it with signed trust checks.

Governance standard and reference toolset for LLM-maintained knowledge corpora

Approval gate and audit trail for AI agent actions: policy check first, proof after. Any MCP client.

Recall and calibrate policy-compliant tool-call arguments before execution. Does not run the tool.

Turn a written policy into rules a program can check, and get the same answer every time.

MCP server for Altmetric APIs - track research attention across news, policy, social media, and more

Web step blocked? Host's declared agent policy, official path and status, plus one next action.

Author rules from policy docs, then decide: a Rete engine gives the verdict, an LLM explains why.

Permission-aware retrieval for AI systems: policy-enforced access to organizational knowledge.

The agentic meta-harness — freeze the model, evolve the harness. An open runtime that routes each query to the cost-optimal model, evolves its own harness (planner/context/reviewer/retry/tool/memory/score policy) and autonomously repairs code, then orches

Your personal AI runtime, local-first. Patchwork OS gives any AI model a consistent set of tools, YAML recipes, a delegation policy with approval queue, and a durable trace memory — all on your machine, all under your policy.

Free website privacy scanner for pre-consent cookies, trackers, consent, policy, and HTTPS/TLS.

Model Context Protocol server transport: serve typed procedures as MCP tools to Claude and other MCP clients, with streaming progress, list_changed and an expose policy.

Enables AI agents to drive policy evaluation over MCP by starting executions, answering policy questions from case evidence, and reading deterministic outcomes with reasoning traces, while the runtime controls which questions are asked and how answers combine.

Nornicdb is a distributed low-latency, Graph+Vector, Temporal MVCC with all sub-ms HNSW search, graph traversal, and writes. Using Neo4j Bolt/Cypher and qdrant's gRPC means you can switch with no changes while adding intelligent features like schemas, managed embeddings, reranking+llm, GPU accel, Auto-TLP, Policy-based Memory Decay, and MCP server.

SceneScout — exploratory UI testing for AI coding agents. An MCP server that gives any agent (Claude Code, Cursor, VS Code Copilot, Codex, Gemini CLI and others) a structured view of a running web app, always-on oracles, a network-level write policy, memo

Enables AI agents to make policy-scoped payments with spending caps, recipient allowlists, approval thresholds, instant revocation, and an append-only audit trail in a sandbox wallet.

Enables MCP clients to query a sensitive local workspace through a read-only status bridge that returns only pre-defined numeric file counts, status enums, and static policy—never source, paths, diffs, logs, environment variables, or command execution.

A gateway MCP server that lets agents reach any upstream MCP server through one endpoint while enforcing policy rules, holding risky tool calls for human approval, containing prompt-injected sessions, and logging every call.