"Answer Engine Optimization (AEO) Audit Guide" matching MCP servers:

Transparent Go proxy that intercepts, signs, rate-limits, redacts, and audits all MCP JSON-RPC tool calls without modifying client or server. Stores to JSONL or SQLite with HMAC-SHA256 signatures.

MCP Server for Kubernetes Audit Logs.

MCP server for managing and serving dynamic prompt templates using elegant and powerful text template engine. Create reusable, logic-driven prompts with variables, partials, and conditionals that can be served to any compatible MCP client like Claude Code, Claude Desktop, Gemini CLI, etc.

Enables governed multi-agent software factory operations through eight typed, audited tools for Sprint planning, submission, decisions, inspection, cancellation, and resumption.

I gave Claude a mass grave of 200 markdown files and now it remembers my entire project between sessions. No cloud, no API keys, one 10mb Go binary, and private. Stateless Agent Memory Engine is your synapse to the CLI.

Enables coding agents to develop on one machine and verify results on another, using branch-bound runbooks, isolated checkpoints, and structured receipts to guide repair iterations.

Scans self-hosted, multi-tenant AI-agent platforms for tenant-isolation gaps. Native Go MCP server exposing a scan tool that wraps the CLI's audit engine.

LLM Optimizer is an AI visibility intelligence platform. It analyzes how large language models and AI search engines perceive, cite, and recommend brands; then provides research-backed optimization strategies to improve that visibility.

Enables LLMs to access banking, investment, and cryptocurrency data through a standardized MCP interface, featuring Plaid integration for account and transaction data and Robinhood for crypto trading with audit trails.

Enables coding agents to show mockups and diagrams in a browser tab for a human to review and click, then reads those clicks back to guide visual brainstorming sessions.

Production-grade MCP Gateway in Go featuring dynamic OpenAPI tool registration, RBAC governance, in-flight PII/DLP redaction, and structured JSON audit logging.

An MCP server that exposes tools for issuing scoped agent credentials, delegating narrower child credentials, handling approvals, revoking task trees, and retrieving audit trails and evidence packets.

Radar is an open-source Kubernetes observability and diagnostics MCP server. It exposes cluster health, workload diagnosis, logs, events, topology, audit findings, and remediation actions to AI agents through the Model Context Protocol.

Local CI/CD engine for AI agents. ActionD listens to LGH git events and runs plugin jobs (Go/Python/Java/web toolchains) in isolated checkouts, with structured results, root-cause failure diagnosis, approval gates, and auto-rollback. The MCP server exposes 23 tools, including dev_cycle_run (commit → CI → structured verdict in one call) and actiond_diagnose for failed-job analysis.

Read-only attack-path tools for cloud and Kubernetes: list the reachable routes from internet exposure to sensitive assets, explain each hop and the evidence behind it, and simulate a fix before recommending it. Connects to a running PerspectiveGraph engine.

Adds security capabilities like port scanning, TLS inspection, DNS enumeration, process monitoring, secrets scanning, HTTP header auditing, and CVE checking to Claude Code and Cursor.

Persistent memory engine for AI coding agents. Single Go binary, zero runtime dependencies, MCP-native. Stores, searches, and deduplicates memories across sessions using embedded SQLite with hybrid FTS + semantic search, memory decay, relation graph, and token-budget context assembly.

SuperDev is a local-first desktop app + MCP server that gives AI coding agents (Claude Code, Codex, Cursor — anything MCP-compatible) access to the runtime: live and historical logs across services, breakpoints in already-running processes (same PID, no restart), real browser control, and DAG deploy pipelines — with human approval and an audit trail on protected writes.

Content-addressed code graph that produces ranked context for AI agents in one call. 22 MCP tools across indexing, blast radius, test scope, semantic diff, runtime traffic, and feedback-aware context packing. Incremental updates via Merkle DAG (no re-indexing). GCF wire format saves 84% tokens vs JSON

Open-source MCP proxy that enforces security policies, content scanning, and audit logging between AI agents and tool servers