"Bitcoin SV" matching MCP servers:

MCP server for microservices.sh that enables planning, inspecting, composing, validating, and deploying microservices modules and templates with preview deployments.

A Model Context Protocol (MCP) server that provides Xcode-related tools for integration with AI assistants and other MCP clients.

Generates VS Code installation buttons and markdown badges for MCP servers, supporting both Stable and Insiders versions with configurable inputs and commands.

MCP server to manage Adila platform via natural language, enabling deploys, logs, metrics, and infrastructure mutations through CLI AI clients.

Enables MCP-capable AI agents to safely read and write ServiceNow records via the Table API, including querying, creating, updating records, running server-side scripts, and triggering CI/CD tests and scans.

A secure MCP server providing controlled access to pixi tasks and commands, eliminating agent bash circumvention. It exposes 11 pixi tools through 4 meta-tools for ~95% context savings.

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Read-only MCP server for VecheMoga, enabling AI assistants to query PostgreSQL, inspect logs, and check API delivery status.

Connects AI coding assistants to Gaffer test history and coverage data to analyze project health, debug failures, and identify untested code areas. It enables tools to track test stability, cluster failures by root cause, and monitor code coverage trends across projects.

Enables AI coding agents to see their Odoo.sh projects by listing projects, branches and builds, waiting for a build to finish, reading build and server logs, and optionally rebuilding branches or updating the firewall. It runs read-only by default with bounded, time-limited tool calls, keeping the user's Odoo.sh session out of the agent's reach.

Replay-verified minimal JSON reproductions and deterministic TypeScript/OpenAPI drift checks. Local-first CLI and MCP server.

SSH-based Model Context Protocol server for Odoo.sh - Build custom apps with AI assistance using Git workflow tools.

An interactive tool that enables users to benchmark vLLM endpoints through MCP, allowing performance testing of LLM models with customizable parameters.