deep, reliable and confidential coding-context

Zero-custody DeFi intelligence and control MCP server for AI agents, exposing Trail Heat, wallet and risk intelligence, swap and futures workflows, x402 access, and policy-gated execution. FarmDash never receives customer private keys.

Enables agents to query real-time GPU rental prices across 26 platforms, including current lowest quotes, 30-day price history, market movers, platform reliability, and task/budget recommendations. Access is read-only and metered per call via x402 with USDC on Base, requiring no signup or API key.

Enables stateless, pure-visual control of Android devices and emulators through adb shell, providing screen capture, coordinate-based taps, swipes, keyboard input, and arbitrary adb command execution for agent-driven interaction.

An MCP server that enables AI clients to inspect footage and audio, edit revision-locked timelines or generated source code, render with Remotion or HyperFrames, and verify results through measurements for iterative video editing.

A hosted remote MCP server that gives AI agents live hotel, Airbnb/Vrbo and flight pricing tools — nightly rate calendars up to 330 nights, every booking site's price for a stay compared against the hotel's own site, guest reviews, and Google Flights search. Clients connect over Streamable HTTP with browser OAuth or an API key, so nothing needs to be installed or run locally.

Enables agents to retrieve permission-filtered document knowledge across organizations and knowledge bases, and to identify and expand business terms and typed object relationships through a unified MCP interface.

Enables developers to register custom tool-calling functions, execute path-safe file operations within an isolated workspace, and keep in-memory memory and audit state for AI agent workflows.

Provides Model Context Protocol access to the SEAF ArchTool REST API, enabling agents to inspect sections and entities, navigate relations, query datasets, and run JSONata expressions against a SEAF portal.

Enables VS Code Copilot Chat and custom agents to perform MongoDB queries, writes, transactions, schema discovery, index and collection management, and administrative commands across multiple secure connection profiles without using mongosh or PowerShell.

Gives browser agents a reviewed map of 79 real sites — entry URLs, access verdicts, and role/accessible-name button maps for 104 screens — so an agent can find where things are and know whether it may act at all. Safety rules in code halt irreversible actions such as pay, order, submit and delete pending explicit human approval, while per-site memory recalls which routes worked last time.

Enables an AI agent or any MCP host to discover and call keyless web search, safe arithmetic, constrained HTTP fetching, and current-time tools over stdio, with model tool-calling powered by Groq's free API or local Ollama.

Exposes an assess_repo tool that scans a repository, local folder, or npm/PyPI package and returns supply-chain risk findings with file, line, and code evidence — install-time scripts, dangerous patterns, secrets, AI-agent manipulation, impersonation and published-artifact mismatches — while never executing the target's code. Findings carry severities from info to critical so results can gate installs and CI jobs.

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 a single owner to run a self-hosted authenticated MCP server that adds Slack reading and replying, Outlook inbox and calendar lookup, signed Slack event capture, restricted KakaoTalk Windows-agent tasks, appointment tracking, and morning briefings to an existing MCP setup.

Enables MCP clients to classify free-text purchase descriptions into United States federal procurement codes and submit authorized, idempotent reviews through typed tool contracts.

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 AI assistants to inspect PostgreSQL schemas and table metadata, preview SELECT queries with capped rows, and receive write or DDL statements for manual review without execution.

Exposes a governed dbt MetricFlow semantic layer to AI agents through three tools — list metrics, list dimensions and query metrics — so questions about federal contract spend are answered from defined metrics rather than raw tables. Guardrails reject undefined metrics, raw columns, SQL in filters and bulk exports, and no tool can execute SQL.

Turns any OpenAPI 3.x spec into an MCP server that exposes one validated tool per API operation, so AI agents can discover and call a REST API over stdio or Streamable HTTP. It is read-only by default, with allow/deny lists, environment-based auth, timeouts and response truncation for safe agent access.

Enables an AI agent to see and control the screen of an already-running macOS virtual machine over VNC, exposing four tools: screenshot, click, type_text, and key_press. This lets the agent drive a disposable VM's UI directly with its own model, without touching the real desktop or running a separate agent loop.

Enables MCP clients to query and diagnose machine-learning training runs through read-only tools for listing experiments, reading configurations and final metrics, comparing runs, sampling metric curves, and detecting training failures.

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 AI agents to write, compose, and check assume-guarantee contracts, including refinement, consistency, compatibility, realizability, and LTL checks, and to use returned counterexamples to fix specifications.