llm MCP servers & tools

Hindsight: Agent Memory That Works Like Human Memory - Built for AI Agents to manage Long Term Memory

An MCP server that bridges to multiple OpenAI-compatible LLMs - your AI rubber duck debugging panel for explaining problems to various AI "ducks" and getting different perspectives

Connect Claude to any OpenAI-compatible LLM endpoint and offload routine work to a local model.

Use natural language to explore LLM observability, traces, and monitoring data captured by Opik.

Chat with OpenAI models from Claude Desktop

AI API cost tracking and budget enforcement across 11 LLM providers. 6 tools for spend analytics, budget monitoring, session summaries, and key management.

Query Langfuse traces, debug exceptions, analyze sessions, and manage prompts. Full observability toolkit for LLM applications.

Pool 18 LLM providers through MCP: ask, panel, tokenmax, route, models, quota, and stats.

Invoke deployed LLMGraph no-code LLM workflows (chat, RAG, automations) as MCP tools.

An MCP server that enables cross-LLM communication and memory sharing, allowing different AI models to collaborate and share context across conversations.

Generate QA datasets & evaluate RAG systems. Privacy-first, any LLM, local or cloud.

Synap (pool.linkrra.com/v1), Linkrra's OpenAI-compatible LLM API, as an MCP server.

Multi-LLM deliberation with anonymized peer review. Runs a 3-stage council: parallel responses → anonymous ranking → synthesis. Based on Andrej Karpathy's LLM Council concept.

Synthetic monitoring for LLM inference endpoints. Measure TTFT, latency, throughput, and errors across OpenAI, Anthropic, Google, Azure, Bedrock, and local servers (vLLM, SGLang, Ollama). CLI + MCP server with Prometheus and OpenTelemetry export.

Local-first LLM API cost tracker. Captures usage across Anthropic, OpenAI, Qwen, and DeepSeek into a local SQLite ledger and exposes spend queries, provider comparison, and recommendations as MCP tools — with first-class Chinese-provider support (CNY→USD). Install: uvx llm-usage-mcp.

Bridge to local Ollama LLM server. Run Llama, Mistral, Qwen and other local models through MCP.