PyPI (Real-time)
ActiveReal-time PyPI feed for AI/MCP packages
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atoti-server-ai-openai
ActiveViam
Resources to use OpenAI with Atoti
kuafu-llm-infra
LLM infrastructure layer with multi-provider fallback, health monitoring, speed probing, and alerting.
zopyx.llm-moonshot
NickMystic
Run prompts against LLMs hosted by Moonshot
atoti-client-storage-azure
ActiveViam
Code to load data from Azure Blob cloud storage
unchainedsky-cli
Browser automation CLI over local Chrome CDP — DDM-first methodology for LLM agents
towelette
A tiny RAG to wipe away API hallucinations
sprout-social-mcp
MCP server for managing Sprout Social via Claude
rag-pathology
Diagnose RAG pipeline failures by type and location. Four Soils classification. Epistemic mismatch detection.
dominion-observatory-langchain
Dominion / vdineshk
LangChain / LangGraph integration for the Dominion Observatory — auto-report MCP tool calls and pre-flight trust-score gate any LangChain tool.
...morequantpipe
Your Name
Quantitative trading toolkit for LLM AI
aigis-cli
AI governance guardrails for coding agents. Framework-aligned security and compliance patterns from NIST AI RMF, OWASP Top 10 for LLMs, and ISO/IEC 42001.
...moresap-datasphere-mcp
Mario DeFelipe
Model Context Protocol server for SAP Datasphere integration with 48 tools. Supports stdio and Streamable HTTP transports.
...moreprivacyforms.ai
PrivacyForms AI - LLM integration module
fastapi-mcp-router
Lightweight FastAPI integration for Model Context Protocol (MCP)
enact-langchain
ENACT Protocol
LangChain tools for ENACT Protocol — trustless escrow for AI agents on TON
llmux-py
A simple library to call various LLM providers.
influ2-mcp
MCP server for Influ2 person-based advertising platform — manage campaigns, audiences, and creatives through natural language
...morellm-forge-new
Config-driven, YAML-first open-source LLM training platform
minibotclaw
zyren123
A minimal, framework-free AI agent toolkit for learning, local automation, and MCP-powered workflows.
bridgic-amphibious
Bridgic-cognitive has implemented an amphibious execution model: the same system can operate in both LLM-driven agent mode (on_agent()) and deterministic code-driven workflow mode (on_workflow()), and can switch between the two modes autonomously when necessary.
...more