"Abaqus Finite Element Analysis Software" matching MCP servers:

Enforces structured, evidence-guided software engineering tasks with cognitive actions (investigate, plan, verify, remember) and persistent state for LLM-based coding agents.

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

Haft is an MCP server that enforces engineering discipline for AI-assisted software delivery, providing tools for problem framing, decision contracts, and commission-based execution harnesses.

PCI DSS v4.0.1 compliance scanner for Go payment services, delivered as an MCP server. Every finding maps to a specific PCI DSS requirement ID. Taint-aware cardholder data flow analysis with PCI SSC FAQ semantics, designed to complement broad SAST tools like Semgrep and CodeQL - not replace them.

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.

MCP server that keeps language server sessions warm and routes multiple languages through one process. Agents get persistent cross-file awareness, speculative execution (simulate edits before writing to disk), and 20 skills that encode correct multi-step operations like safe rename, blast-radius analysis, and end-to-end refactoring. Single Go binary, no runtime dependencies.

A fast, lightweight MCP server and CLI for Obsidian vaults built in Go. 16 multiplexed tools covering 72 actions for notes, search, templates, tasks, links, frontmatter, and vault analysis. Single binary, no plugins required.

Enables AI coding agents to query a semantic cross-repository code graph for symbols, references, callers, dependencies, and change impact across registered repositories.

Connect Legacy Databases to AI Agents via Model Context Protocol. Open-source bridge for LLM data analysis.

Local-first code intelligence for AI coding assistants: MCP tools, symbol graph search, impact analysis, and auto-index watch for Cursor, Claude Code, and Codex.

An MCP server that provides Claude Code with 99 methodology skills, seed patterns, decision logging, and memory tools to improve software development decisions. It acts as a cognitive scaffold layer, enabling better working methods rather than just additional data.

Enables AI agents to query cluster-wide network traffic, investigate API calls, and perform root cause analysis using natural language, with access to decrypted TLS traffic and Kubernetes context.

MCP server that lets LLMs interact with a running Prometheus instance via its API, enabling metric analysis, PromQL queries, and rule/target inspection. It also provides embedded documentation and guided runbooks for common Prometheus tasks.

Enables AI agents to inspect and operate multiple Kubernetes clusters through natural language, providing multi-cluster diagnostics, RBAC analysis, security checks, and app-centric deployment with GitOps and smart workload placement.

Code-pinned team memory for AI coding agents — typed artifacts (Decision/Analysis/Debug/Task), MCP-native workflow, self-host with Docker Compose.

Provides AI coding assistants with code search, impact analysis, task chaining, and persistent memory to turn AI demos into deliverable code.

Enables AI assistants to control Pi-hole DNS filtering, including domain management, query analysis, and system administration, with support for multiple Pi-hole instances and synchronization.

Connects AI tools to GitHub and local git repositories, enabling natural language management of issues, PRs, code analysis, and workflows.

Enables AI assistants to automatically call Carbonstop Cloud API for carbon footprint modeling, product query, and emission analysis through natural language.

A local MCP server that indexes codebases into Neo4j and provides tools for code analysis, dependency visualization, and impact assessment.