"MEGA" matching MCP servers:

MCP server for MEGA encrypted cloud storage providing file management, uploads, downloads, sharing, folder sync, and search.

Enables AI agents to perform accurate local computations including arbitrary-precision math, date handling, unit conversion, subnet calculations, encoding, hashing, and text analysis, all without network calls or API keys.

An MCP server that lets coding agents build and query a persistent knowledge graph of concepts, architecture, and decisions, enabling them to remember across sessions.

Enables AI to dynamically discover and invoke any Cin7 Core API endpoint using three generic tools (list, describe, invoke) plus a bug-report tool, covering the entire API surface without predefined endpoints.

Enables running bpy Python code in an already-open Blender instance, with tools for health checks, scene info, and viewport screenshots.

Enables users to learn the full path for connecting a WhatsApp number to Meta's official Cloud API—including virtual numbers and Coexistence—and diagnose each onboarding phase with Graph API checks.

Enables building and iterating on a software company through natural language, returning live preview URLs, without needing a browser.

Provides AI assistants with access to Vega-Lite documentation, visualization examples, and specification validation tools. Enables searching docs, retrieving examples by category, validating JSON specs, and accessing schema information for creating data visualizations.

Enables AI coding assistants to share persistent local memory across sessions and agents, so rules, mandatory specs, verified code snippets, and past mistakes are automatically surfaced before code is generated. It also lets agents log repeated failures as recurrence-counted 'vaccines', preventing the same errors from recurring across Claude, VS Code agents, and local LLMs.

Enables running MegaLinter linting, configuration, and analysis through MCP tools. Works with any CI/CD platform or locally.

A tool that dynamically generates and configures MCP servers by automatically creating necessary directories and files according to user specifications.

A Model Context Protocol server that enables AI models to interact with GitHub's API, allowing for repository creation and management with descriptions, topics, and website URLs through natural language commands.

A meta API Gateway server that works with the Model Context Protocol (MCP), enabling AI assistants to connect to any API and access real-world data sources through standardized MCP tools.

Enables agents to generate typed client code from OpenAPI, GraphQL, Protobuf, and SQL specs using MetaEngine's code-generation platform.

Enables multi-model AI code review from inside supported coding tools, reporting where up to four models agree and disagree.

Automates codebase review and documentation generation using specialized AI agents, integrating with MCP for AI workflows and Smithery for deployment.

Enables AI agents to operate and view the Vega Virtual Device through MCP: press remote keys, take screenshots, record video with sound, wait for screen changes, and check the TV safe area.

Enables AI agents to inspect, create, and edit 1C metadata and managed forms in a configurator XML dump without manual XML editing, using metadata_check for dry-run validation and metadata_apply for writes. It enforces platform dump rules, preserves formatting, and supports operations such as object creation, property changes, renaming, role generation, and form amendments.

Enables an MCP server to gate tools/call requests by requiring a per-send channel-policy attestation for outbound actions, checking ROPE-lite origin tags on sensitive arguments, and returning SEP-2643-shaped structured denials with retry handles and remediation hints when a call is blocked. It logs client-asserted audit context (such as turnId and userIntent) for correlation across allowed and denied calls, but never uses that receipt for allow/deny decisions.

Deployable MCP clone services for A2A-Meta, hosting pending clones via a multiplexer for Railway deployment.

Unifies local Agent Skills from DSH, Claude, Codex, Magpie, and shared agent directories behind a single lazy-loading facade, exposing three tools to search, list, and load skills on demand. It keeps system prompts lean by fetching full SKILL.md instructions only when a task needs them, and returns local paths so bundled references, scripts, and assets stay reachable.

Enables pi coding agent users to run Pega Infinity authoring tools as native pi tools, with read-only access by default and write tools behind an explicit opt-in flag.

Turns any OpenAPI specification into an MCP server exposing three tools to search operations, inspect one operation's parameters and request body, and call it via HTTP. This keeps the tool list small while making every API operation reachable, with auth headers supplied from environment variables and hidden from the agent.

Provides a semantic search interface that enables discovery and routing across over 1,000 local MCP tools using natural language queries. It leverages hybrid search and embeddings to accurately match user intent with tool names and descriptions.

An MCP server that exposes authoritative, read-only Conda ecosystem metadata for AI agents, enabling package search, dependency resolution, and other packaging queries without side effects.

Enables users to run queries across multiple AI models in parallel, comparing latency, token speed, and cost, and to integrate this multi-model racing and code review capability into Claude Code, Cursor, and Codex CLI.

Enables creating and editing live, interactive dashboards with Vega-Lite charts via A2UI in MCP hosts, with dataset binding and reusable widgets.

A flexible proxy that enables discovery and execution of tools across multiple Model Context Protocol (MCP) servers and JavaScript functions, reducing context size even when dealing with hundreds of tools.

Enables MCP clients to access many upstream MCP servers through two lazy tools that list and call tools, fetching schemas only when needed to reduce per-request schema overhead.

Provides AI assistants with comprehensive access to WordPress Meta Trac data, enabling intelligent queries about WordPress.org infrastructure, plugin/theme directories, WordCamp events, and other WordPress.org services through ticket searches, changeset information, and activity monitoring.

Enables AI coding assistants to discover and configure Meta Developer apps, manage team roles and webhooks, monitor permissions, create test users, and invoke the Graph API directly.

MCP server for searching and analyzing 1C enterprise metadata and BSL code using a SQLite backend. Enables querying configuration structure, code routines, and performing compliance checks via natural language.

Enables the deployment of remote Model Context Protocol servers on Cloudflare Workers without authentication using Server-Sent Events. It provides a boilerplate for developers to add custom tools and connect them to clients like Claude Desktop or the Cloudflare AI Playground.

A Model Context Protocol server that wraps multiple backend servers for token-efficient tool discovery via lazy loading. It enables AI models to browse available servers and fetch specific tool schemas on-demand, significantly reducing initial context overhead.

Aggregates tools from multiple MCP servers, generates TypeScript definitions, and executes custom TypeScript scripts to orchestrate cross-server tool calls.

Enables persistent storage and semantic search of coding preferences, patterns, and implementations using Mem0, allowing AI agents to remember and retrieve development best practices across sessions.

MCP server for exploring Pega branches and fetching full rule XML for LSA-style code reviews.

Enables autonomous agents and multi-agent frameworks to discover and execute modular, class-based tools over SSE with a standardized response contract.