"WP Engine" matching MCP servers:

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.

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.

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.

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.

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 SQL-native query and provisioning engine for cloud and SaaS infrastructure. Ships as a single signed binary with MCP tools for provider discovery, schema exploration, queries, and lifecycle operations.

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.

self-hosted development harness (Go engine + CLI + desktop, Linux first) · brief → requirements → spec → plan → build → review → release · verdicts are exit codes, never model opinions · local models first (llama.cpp, vLLM) beside any OpenAI-compatible or Anthropic endpoint · operable by humans or by other agents over MCP with recorded, attributed decisions

Enables AI agents to interact with WhatsApp through a safety-first MCP server, with tools for sending messages, media, searching chats, and managing drafts, all governed by default-deny allowlists and non-overridable rate limits.

High-performance code graph and code intelligence engine. Index code base into knowledge graph, supports 257 languages and native multi repositories environment

Guardrail sidecar proxy between AI agents and their MCP/REST/CLI tools. Policy engine, human approval gates, time-limited grants, rate limiting, and OTEL tracing. One Go binary, one YAML config, fail-closed by default.

A typed, policy-controlled OS capability layer for AI agents via MCP, exposing safe filesystem, git, and text-processing tools governed by a strict policy engine.

A sovereign compliance engine with 36,195 STIG/CCI/NIST/CMMC mappings and 76 tools, enabling AI assistants to scan systems, generate risk reports, and ensure post-quantum cryptographic attestation—all air-gappable with zero token costs.

Enables LLM agents to play six-on-six Pokémon battles with hidden information, a full move set, and a deterministic battle engine, including local play, reproducible matches, and benchmarking against AI opponents.