Packages

mcp-name: io.github.wmarceau/rideshare-comparison

A quick pokemon demo to showcase MCP server, client, and host

markdown to card

[](https://smithery.ai/server/@MeasureSpace/measure-space-mcp-server)

An MCP (Model Context Protocol) server that identifies biological species from images, returning Latin names with confidence scores.

MCP server for OriginalVoices - Ask AI twins questions about any audience

MCP server for OriginalVoices - Ask AI twins questions about any audience

Query OpenAI models directly from Claude using MCP protocol.

A MCP server to connect to wolfram alpha API.

semantic-router is a Python decision/routing layer that selects a route (e.g., intent, task, tool-use path) by embedding the incoming utterance(s) into a vector space and matching them against route utterance embeddings, returning the best-matching Route (or None if no match). It supports multiple encoder backends (e.g., OpenAI, Cohere, Hugging Face, FastEmbed, local/HF+Torch/llama-cpp) and can integrate with vector indexes such as Pinecone and Qdrant; it also advertises multimodal routing via optional vision/multimodal paths.

mcp-name: io.github.ysydhc/team-memory

MCP server to pull status from Linear

A Model Context Protocol (MCP) server for accessing Data Commons API data.

This is a POC of how you can build an MCP servers on top of Uber Eats

PostgreSQL-backed tool that transforms compressed Reddit/Voat/Ruqqus data dumps into searchable HTML archives with full-text search, REST API, and an MCP server with 29 tools for AI assistant integration.

deepeval is an open-source Python framework for evaluating LLM apps (e.g., chatbots, agents, RAG pipelines). It provides a test/pytest-like workflow and many ready-to-use evaluation metrics (including LLM-as-a-judge metrics such as G-Eval, RAG metrics, agent/tool metrics, multimodal metrics). Metrics can run locally (using the chosen models) and it can integrate with CI/CD and common LLM app frameworks (OpenAI, LangChain, LangGraph, LlamaIndex, CrewAI, etc.). It also offers a hosted “Confident AI” platform option with CLI login and a stated MCP server integration for persisting data/traces.

LMQL (Language Model Query Language) is a Python superset and runtime that lets you embed LLM calls directly inside code, using templated variables plus decoding algorithms and constraints (e.g., logit masking, datatype/format constraints, stopping conditions). It supports sync/async execution, multi-model backends (e.g., OpenAI, Azure OpenAI, HuggingFace Transformers), and includes tooling such as a playground and an inference API for serving models.

Namecheap's XML/REST API for domain registration, DNS management, WHOIS lookup, SSL certificate management, and domain portfolio management.

SAP's OData and REST APIs for accessing enterprise business data including finance, procurement, supply chain, HR, and customer management across SAP S/4HANA and SAP BTP.

Slack integration for OpenClaw/Clawd agents