"Connecting Feishu (Lark)" matching MCP servers:

Automates GitHub Pull Request analysis using AI, integrating webhooks, OpenAI, and Feishu/Lark knowledge base for structured summaries.

High-performance Model Context Protocol (MCP) server connecting Claude Code and AI agents to Google Gemini 3.8 Flash, Gemini 3.1 Pro, reasoning effort, and image generation.

Enables Claude to explore, analyze, and answer questions about any public GitHub codebase by connecting to DeepWiki's AI-powered documentation.

MCP server connecting Claude Code to LM Studio, delegating token-expensive tasks to a local model while keeping the cloud model in control. It reduces cloud context usage by reading files locally and returning only the processed results.

Enables AI assistants to build complete, live websites from natural language descriptions by connecting to Buildez.ai.

Enables connecting Blender 3D to AI assistants via MCP, allowing prompt-driven 3D modeling, scene editing, and real-time manipulation. Supports object/material control, scene inspection, viewport screenshots, and integrations with Poly Haven, Sketchfab, and AI model generators.

Connecting to the ReviewMetric, 15-AI agent scientific peer review pipeline

Enables MCP-compatible AI applications to translate text through the Lara Translate API, with automatic language detection, context-aware translations, and custom instructions.

Enables MCP-compatible AI applications to translate text between many languages, with automatic source-language detection, contextual hints, and custom translation instructions.

Enables MCP-compatible AI applications to translate text between languages with automatic language detection, contextual hints, custom instructions, and multi-language support.

Enables AI applications to perform multi-language translations with automatic language detection, contextual hints, and custom instructions through an MCP-compatible interface.

Enables AI applications to translate text through the Lara Translate API, with automatic language detection, context-aware translations, and custom instructions.

Enables AI applications to perform text translation across numerous language pairs with automatic source-language detection, contextual hints, and custom instructions.

Python MCP adapter connecting Claude/Cursor/Cline to the OpenAaaS scientific agent network.

Enables agents to orchestrate and call tools across HubX's mobile AI app portfolio for multi-model chat, plant/vision diagnostics, generative image and design, nutrition tracking, audio note summarization, language tutoring, and wellness workflows through a unified MCP interface with structured JSON output.

Enables statistical forecasting and anomaly detection over numerical time-series data using Holt linear smoothing, multi-step projections, and variance-based confidence bands.

A Python MCP server using the Falcon web framework, providing Streamable HTTP transport for connecting AI agents and MCP clients.

Enables edge AI agents to optimize inference memory and latency by mapping logical blocks to non-contiguous physical pages, tracking fragmentation, and exposing related MCP tools.

Enables agents to perform symmetric INT8 per-tensor and per-channel quantization of LLM weights and activations, returning SNR and MSE reconstruction metrics for edge inference optimization.

Enables sending real-time and webhook notifications when AI agents complete tasks, with support for Discord, Slack, Teams, Feishu, Ntfy, and custom webhooks.

Enables MCP-compliant clients and autonomous agents to pick optimal few-shot in-context exemplars by combining semantic token overlap, cosine similarity, and Maximal Marginal Relevance diversity ranking for prompt optimization. Runs deterministically on the Python standard library with zero external dependencies, avoiding frontier LLM round-trips for sub-millisecond selection.

Enables inference engines to match longest common prompt token prefixes via a radix trie, so cached KV-cache blocks are reused instead of re-prefilled. This eliminates redundant prefill computation and lowers time-to-first-token, alongside paged attention allocation, speculative decoding verification, INT8 quantization, and latency telemetry.

Enables connecting Claude, Cursor, VS Code, Windsurf, and other MCP clients to Taskade for workspace, project, task, and AI agent management, and for generating MCP tools from OpenAPI specifications.

Enables multi-agent AI collaboration by connecting Claude Code, OpenAI Codex, and Google Antigravity, providing cross-model code reviews, independent second opinions, and autonomous validation through MCP tools.

Enables AI coding agents to autonomously generate images, music, and cinematic video directly from their coding environment by connecting to Google Labs and Google Flow through the user's Chrome session.

Enables agents to verify complex math, code, and logic reasoning through MCTS step-level process reward modeling, counterfactual backtracking, symbolic proof checking, and majority-vote consensus so hallucinated branches get pruned. It also allocates test-time compute dynamically and exposes these capabilities over a zero-dependency STDIO MCP server for Claude Desktop, Cursor, and other agent runtimes.

This MCP server enables AI-assisted professional profile generation by connecting to verified employee work data (skills, career history, certifications, projects) from employer HCM systems.

Enables users to perform multivariate linear regression with gradient descent, Holt linear forecasting, Welch's t-test evaluation, anomaly detection, and PCA dimensionality reduction through MCP-compatible clients using only Python standard library tools.

A lightweight, air-gapped desktop cockpit connecting local LLMs (Llama 3.2) to standard MCP tools with deterministic hardware safety, acting as an edge-native MCP control plane and autonomous tool dispatcher.

Enables managing AI voice agents, phones, integrations, workflows, calls, and billing directly from chat, including editing agent settings, connecting CRMs, and reviewing call logs.