Enables AI assistants to build and configure Cisco Packet Tracer topologies, run device and connectivity commands, and inspect simulation-mode packet explanations through natural language.

Enables MCP clients to build and troubleshoot Cisco Packet Tracer networks by adding devices, cabling them, pushing IOS configurations, addressing interfaces, configuring routing, running pings, and reading/writing .pkt files without Packet Tracer open.

Crypto perps for AI agents: funding, OI, liquidations, order book, CVD, volume profile, footprint.

Framework-aware code intelligence MCP server — 91 framework integrations, 81 languages, 72.7% fewer input tokens to review a pull request, comprehension at parity

Open-source manufacturing ERP, MES and QMS. Quoting, MRP, inventory, shop floor, quality and lot/serial traceability on one Postgres schema, with a REST API and MCP server. Self-host or use Carbon Cloud.

Structural memory for AI coding agents. Bi-temporal graph, MCP-native, zero LLM calls. Cursor · Claude Code · Codex · DeepSeek Harness · Hermes · VS Code · Windsurf.

Mirror your body in data. One standard, every source, one complete picture of you: a self-hosted health record built from lab reports, wearables and genetics, with every number traced to its source and a built-in MCP server. Run it with Docker and one LLM key, or keep every model local on llama.cpp.

Local deterministic memory and safety kernel for AI agents. Replaces vector RAG with STRATA, a cryptographically signed, append-only ledger, so every agent state carries proof. Uses causal_walk engine to trace execution failures back to their root cause, and Operator Lite to block destructive terminal terminal commands before they ever run

Every number in an AI answer traces back to the rows that produced it.

OSINT investigations with traceable evidence: domains, URLs, IPs, scams and business records.

Read LogBrew errors, slow traces, logs, and product analytics, and triage issues with consent.

Query your AI agents' traces, errors, cost and alerts in Rius, the agent observability platform.

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.

Read your Condux issues, events and stack traces (deminified with source maps). Triage optional.

Read the logs, metrics, and traces of the app you are editing, from the Loggerhead Mac app.

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.

Drives the local Doubao desktop client through its DevTools interface, letting an agent read and send chats, run task-mode work, hand off a project directory and take it back, and call Doubao-only capabilities like image generation and step traces. Also borrows Doubao's built-in skill set for cross-checking and project handoff, with a UI badge showing which side currently owns the work.

Enables keyword search across source-traceable evidence chunks, listing opportunities linked to supporting evidence, and deterministic ROI calculations with model-proposed inputs and TypeScript-computed dollar figures.

Gives AI agents a real Chromium browser via Playwright to QA-test web apps, with pass/fail assertions, network mocking, recorded traces and reports, and safety guards that block live payment traffic. Test outcomes come back as explained verdicts suitable for review or email delivery.

Embeds a runtime MCP inspector in a NestJS app so coding agents can inspect the module and provider graph, routes and their guards/interceptors/pipes/filters, logs, request traces, event listeners, and scheduled jobs through an HTTP endpoint.

Enables local, evidence-led analysis of a master recording into inspectable stems, timing, beats, harmony, lyrics, MIDI and sonic evidence, then finds complete-bar loopable sections for Shorts and other short-form video. Results stay traceable through source hashes, manifests, JSON/TSV/NPZ artifacts and portable Sonic Visualiser sessions, and it can run as a CLI, Python library, web service, container or MCP plugin.

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.

Voxel editor with an MCP server: build and edit MagicaVoxel .vox models, add bones and animation clips, run Rhai generator scripts, path-trace PNG previews, and export glTF.

Provides OAuth-secured MCP tools for working with private, Git-backed Markdown knowledge bases: searching pages, reading content, ingesting new source documents, retrieving cited original files, and reviewing history or rolling back accepted pages. Every tool call is checked against each person's or agent's current wiki grant and returns source paths and Git revisions for traceability.