"sage active" matching MCP servers:

Safe MCP server for math operations: evaluate, simplify, and differentiate expressions with configurable precision, using a sandboxed worker thread and strict AST allowlist to block dangerous input.

An MCP server that provides tools for getting second opinions or detailed code reviews from Gemini 2.5 Pro by embedding file contents in prompts, allowing it to handle large codebases with extensive context.

Enables an MCP-compatible AI client to author Blender Python, run Blender, import the resulting asset into Unity with materials and a prefab, place it in the active scene, verify the import, and revise the same asset using stable IDs.

Enables agents to synthesize typed MCP tool schemas at runtime, validate Python ASTs for unsafe imports, compile sandboxed callable handlers, and hot-plug them into an active MCP runtime. It provides a zero-dependency, standard-library-only MCP server for safe just-in-time tool creation and execution.

Enables agents to dynamically generate typed MCP tool schemas, validate Python execution ASTs against unsafe imports, and hot-plug sandboxed callable handlers into an active runtime. This allows new tools to be synthesized and safely executed on demand.

VS Code extension that bridges local Jupyter Notebooks with AI Agents via MCP, enabling direct control of the active notebook tab.

Enables AI agents to run untrusted, model-generated Python code in a locked-down throwaway Docker container with enforced isolation and resource limits. Supports starting, checking, and stopping asynchronous runs while returning structured status reports without exposing the host, network, or Docker controls.

Enables AI assistants to write, validate, debug, and execute AutoHotkey v2 scripts on Windows, with tools for syntax checking, script execution, active window inspection, library search, and live debugging via DBGp protocol.

Enables an agent to open a tldraw.com board in a controlled Chrome tab and draw on it by executing JavaScript against the page's own editor, so edits sync to the shared board. It also captures PNG exports of the view, page, selection, or specific shapes.

BloodHound-MCP-AI is integration that connects BloodHound with AI through Model Context Protocol, allowing security professionals to analyze Active Directory attack paths using natural language instead of complex Cypher queries.

Stdio MCP Server wrapping custom Python runtime (LocalPythonExecutor) from Hugging Faces' smolagents framework. The runtime combines the ease of setup (compared to docker, VM, cloud runtimes) while providing safeguards and limiting operations/imports that are allowed inside the runtime.

Enables Claude Code to work with personal data that stays on the local machine, running SQL, Python, and file/schema inspection in a sandboxed compute-to-data setup that returns only aggregates, schemas, synthetic fixtures, and pseudonymized results. Raw records, file names, and protected values never reach the Anthropic API, so Auto mode can stay hands-off.

Lets an AI agent read and change on-premises Active Directory by writing short JavaScript scripts that run in a network-isolated sandbox against a chosen domain. Runs on Windows as the logged-on user, over Kerberos, with tools for executing scripts, searching the domain's schema catalogue, querying Microsoft Learn docs, and managing domain connections and Group Policy objects.

Enables AI clients to drive SketchUp Pro 2026 on a Windows host, including from WSL, by executing arbitrary Ruby in the active model, reading scene and selection details, and capturing viewport screenshots. It talks to a loopback TCP bridge inside SketchUp using a connect-per-command protocol for reliable, desync-free control.