"Apache Spark" matching MCP servers:

Enables Claude mobile and claude.ai to access your Spark Desktop mailbox by exposing the official Spark MCP server over authenticated Streamable HTTP, with safety gates for read-only and send permissions.

Enables users to access, search, and analyze Spark Desktop meeting transcripts and emails through natural language via the Model Context Protocol.

Enables sending and receiving Telegram messages through MCP clients like Claude Desktop and Gemini Spark.

A standalone MCP server that securely exposes Google Analytics data and Firebase Cloud Messaging capabilities to Spark/Gemini via SSE.

Enables AI assistants to interact with Slack workspaces by listing channels, posting messages and thread replies, adding emoji reactions, retrieving channel history and thread replies, and inspecting user profiles. Supports both stdio and Streamable HTTP transports for flexible integration.

Provides access to UniFi Talk phone system data including call history, timelines, transcriptions, users, devices, and service health, with read-only operations by default and optional write capabilities.

Open-source shared rooms for AI agent conversations across Claude Code, Codex, Pi, OpenCode, and DeepSeek Harness. The Apache-2.0 core provides messaging, room history, MCP integrations, and self-hosting on Cloudflare.

Enables agents to adjust message formality, brevity, tone, and technical depth based on channel context, user cognitive load, and sentiment feedback. It runs as a zero-dependency, MCP-compatible server for consistent communication across interactions.

Enables analysis of multi-speaker meeting transcripts from Tencent Meeting, Zoom, and Teams to extract explicit commitments, dates, and assignees. It prioritizes tasks with an Eisenhower urgency-importance matrix and formats collaborative task cards for WeChat Work dispatch.

Enables AI models to publish and consume messages from Apache Kafka topics through a standardized interface, making it easy to integrate Kafka messaging with LLM and agent applications.

Enables Slack-driven coding agents in isolated cloud sandboxes per thread, with thread-scoped MCP tokens and fail-closed allowlists.

Agentic AI instruction encoding. 86.8% smaller than JSON. Inference-free decode by table lookup. 342 opcodes, 26 namespaces, three conformant SDKs. Confirmed over LoRa mesh radio. Apache 2.0 with express patent grant.

Enables multi-channel inbox message priority classification and response SLA tracking, integrating with MCP-compatible clients such as Claude Desktop and Cursor.

Enables autonomous triage of personal communications and email through deterministic multi-factor urgency scoring, VIP filtering, and context-aware executive auto-drafting. It plugs into any MCP-compliant client to resolve routine communication workflows instantly without frontier LLM round-trips.