Enables MCP-compatible clients to plan, validate, generate, and deploy complete network topologies from natural-language instructions, including live deployment to a running network simulator and export to configuration or script files.

Enables an AI agent to drive a remote Linux machine over the LAN through a single TCP connection, exposing tools for shell commands, jobs, interactive PTYs, file read/write/search/transfer, process and service management, networking, packages, and power control, with optional multi-host switching. Operates without SSH or any Linux-side installation beyond one stdlib-only Python daemon, using a state-free binary protocol.

Enables AI clients to control and inspect a Unity Editor through MCP tools for scene and play-mode operations, logs, screenshots, assertions, Lua execution, UI interaction, world observation, and bridge management; advanced UI/Lua/world features require project-specific adapters.

Enables an agent to verify its own work mid-task by deliberately breaking each changed line, re-running the test suite in isolated workers, and reporting which breaks no test catches, along with a plan tool that previews which changed lines would be checked.

Enables an AI assistant to query Plaid-synced bank data stored locally in SQLite — balances, transactions, spending, cash flow, recurring charges, and liabilities — plus bounded read-only SQL and local CSV/JSON exports, all over local stdio with no hosted service or listening port.

Enables AI agents to connect to Maptek Vulcan 12 Desktop through MCP, allowing natural-language inspection of block models and triangulations, drillhole and CAD database operations, legend updates, 3D screenshots, and PyVulcan script execution.

Enables LLMs to query a local GnuCash MariaDB database through read-only MCP tools for account balances, recent transactions, spending and income by category, transaction search, and net worth without risking data mutation.

A zero-dependency MCP suite exposing computational tools across metabolic, cardio-renal, chronobiology, neuro-recovery, and biomechanics domains. It enables clients to derive longevity and physiology metrics such as autophagy index, glucose-ketone ratio, glycemic variability, peripheral resistance, nocturnal BP dipping, DLMO clock time, melanopic lux, caffeine clearance, EEG fatigue entropy, and grip vitality age from user-supplied measurements.

Exposes MCP tools that compute longevity and metabolic metrics (autophagy index, GKI, MAGE), cardio-renal biomarkers (BUN/creatinine ratio, cardiac output and TPR, nocturnal BP dipping), chronobiology estimates (DLMO, melanopic lux, caffeine clearance), plus neuro-recovery and biomechanics scores. Runs as a zero-dependency Python JSON-RPC 2.0 stdio server so any MCP-compatible client can query these physiological domain calculators.

Enables Alexa+ to turn natural-language household goals into context-aware, confirmation-gated plans, execute them, and verify that devices actually reached the intended state.

Enables querying a Chatwoot support inbox in plain language—finding conversations, contacts, and conversations needing attention—and, after explicit confirmation, adding private notes or updating assignments, labels, and status without sending customer messages.

Enables plain-language queries about a support desk, ticket and customer investigation, and safe, confirmation-gated ticket assignment and internal notes.

Enables asking in plain language about a Proxmox VE cluster's guests, backups, snapshots and resource pressure, and starting, cleanly shutting down or rebooting VMs and containers or taking snapshots from the same chat. Every change requires a one-time confirmation code, and no tool can delete a guest, restore a backup or roll back a snapshot.

Enables natural-language querying of GLPI IT helpdesk and asset data—tickets, ownership, deadlines, and person-held assets—plus safe follow-up additions and ticket updates that require one-time confirmation before changes are applied.

Enables MCP-compatible AI clients to run passive OSINT investigation tools for domains, IPs, emails, usernames, breaches, DNS, WHOIS, and reputation checks through natural-language tool calls. It exposes 16 passive tools by default, plus graph and batch helpers, with additional active tools available when explicitly enabled.

Enables querying a city road graph for shortest routes by total distance and a 25-room maze for fewest-door paths, returning step-by-step trace explanations and animating each search in a live web viewer.

Starts a local stdio MCP gateway that exposes read-only Minecraft Java status and performance diagnostics, safe bounded Spanish gather-request proposals, and non-mutating investigation planning to compatible AI clients.

A read-only MCP server that lets AI agents query a user's own Garmin Connect data via Garmin's official Personal API. It exposes activities, daily wellness metrics, sleep and recovery, and body/profile data as tools for natural-language analysis.

Enables agents to perform autonomous multi-angle specular glare healing and planar foil defect metrology by ranking candidate views, fusing glare-free views, and finalizing inspection or escalating unresolved cases through MCP tools.

Enables Claude to plan search-and-rescue operations on CalTopo maps by measuring terrain, staging areas, hasty search lines, parking, helicopter landing zones, egress routes, walking-time rings, hospitals, and urban assignments, and by exporting results as GeoJSON draft assignments. It is read-only and returns facts for human decision-making.

Enables local management of Pavo website accounts through a stdio MCP service, covering canvases, reference media, generation tasks, result downloads, and website assets. It also supports AI script episode planning plus character, scene, and prop asset management.

Enables MCP clients such as Claude to search, tag, catalogue, ingest, audit, relocate, and repair a running Connecter asset library, including texture scanning and relinking, with dry-run plans and undoable journaled changes.

Enables users to map Türkiye’s free data sources by sector, discover and fetch series, and generate ML-ready monthly Parquet panels through natural language.

Enables converting natural-language mathematical descriptions into rendered Manim animation videos, returning playable MP4 links and reusable code without requiring local Manim, LaTeX, or ffmpeg installations.