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New Server Submission: PanchangaAPI Server name: PanchangaAPI โ Vedic Astrology API Server URL: https://api.moon-bot.cc MCP Manifest: https://api.moon-bot.cc/.well-known/mcp.json OpenAPI: https://api.moon-bot.cc/openapi.json Repository: https://github.com/degen0root/panchangaAPI What does this server do? Complete Vedic astrology (Jyotish) calculation engine with 12 MCP tools: 1. get_panchanga โ Daily Vedic almanac (tithi, nakshatra, yoga, karana, vara, sunrise/sunset) 2. get_kundali โ Full birth chart (Lagna, 9 grahas, houses, aspects, Navamsha, Dasha, Ashtakavarga, Yogas) 3. get_dasha โ Vimshottari Maha/Antar/Pratyantardasha timeline 4. get_compatibility โ Ashtakoot 8-fold marriage matching (score out of 36) 5. get_muhurta โ Electional astrology / auspicious timing 6. get_transits โ Gochar (planetary transits) with Sade Sati detection 7. get_vargas โ All 16 divisional charts (D1-D60) 8. get_shadbala โ Six-fold planetary strength analysis 9. get_bhava_chalit โ House cusp analysis 10. get_prashna โ Horary astrology 11. get_varshaphal โ Tajaka annual predictions 12. get_festivals** โ Hindu festival calendar (astronomically computed) Powered by Swiss Ephemeris with Lahiri ayanamsha. Deterministic, reproducible results. Auth API Key via header Free tier: 2 requests/day (instant registration: ) Paid: USDC via x402 protocol (Base + Solana) Use cases Horoscope generation, birth chart reading, compatibility analysis Financial astrology / market timing Auspicious timing (Muhurta) for events Hindu festival calendar computation
Repository: modelcontextprotocol/servers. Description: Model Context Protocol Servers Stars: 81036, Forks: 9894. Primary language: TypeScript. Languages: TypeScript (70.4%), Python (18.1%), JavaScript (10.3%), Dockerfile (1.2%). Homepage: https://modelcontextprotocol.io Latest release: 2026.1.26 (1mo ago). Open PRs: 100, open issues: 384. Last activity: 6d ago. Community health: 87%. Top contributors: olaservo, tadasant, jspahrsummers, cliffhall, dsp-ant, jerome3o-anthropic, maheshmurag, evalstate, baryhuang, marcelo-ochoa and others.
TypeScript
Summary This PR adds GPU-Bridge to the list of third-party MCP servers. About GPU-Bridge GPU-Bridge is a GPU inference API that exposes 26 AI services as MCP tools through a unified interface. MCP Server: https://github.com/gpu-bridge/mcp-server npm: Services Available LLMs: Llama 3.1 (7B/70B/405B), Mistral 7B, DeepSeek Coder 33B Image Generation: FLUX.1 Schnell/Dev, Stable Diffusion XL, SD 3.5 Vision: LLaVA-34B (visual Q&A), OCR, background removal, image captioning Speech-to-Text: Whisper Large v3, speaker diarization TTS + Voice Cloning: XTTS v2, Kokoro, Bark Audio Generation: MusicGen Large, AudioGen Embeddings: BGE-M3 (multilingual), CodeBERT Video: AnimateDiff (text-to-video), ESRGAN (upscaling) x402 Native GPU-Bridge is the first GPU inference API with native x402 support โ allowing autonomous AI agents to pay for compute on-chain with USDC on Base L2, without API keys or human intervention. Installation Pricing starts at $0.003/request.
Summary Adds observe-instrument-mcp to the community servers list. What it does: An MCP server that automatically instruments Python AI agents with OpenTelemetry-based tracing using the ioa-observe-sdk. It adds , , , and decorators plus and to existing agent code with zero manual effort. Supported frameworks: LlamaIndex, LangGraph, CrewAI, raw OpenAI SDK (single-agent and multi-agent patterns) LLM providers: Anthropic, OpenAI, Google Gemini, Groq, Ollama via LiteLLM Tools: โ reads a Python agent file, applies full instrumentation, writes it back with a backup โ audits a file for missing instrumentation without modifying it PyPI:** https://pypi.org/project/observe-instrument-mcp/ ๐ค Generated with Claude Code