"Lottery games and results" matching MCP servers:

Enables MCP clients to screen lab results against published criteria with deterministic Python, search Australian contaminated-land guidance with cited passages, and draft guarded results sections whose numbers and citations are validated. All four tools are read-only and keep figures and citations under code control for a qualified person to check.

Enables querying DuckDuckGo Instant Answer API for search results.

Facilitates web search capabilities using Perplexity's API, allowing users to retrieve search results through Claude's interface.

Enables LLMs to interact with Oracle Databases by providing specific table and column metadata as context. Users can generate SQL statements and retrieve query results directly through natural language prompts.

Enables natural language querying of Feyenoord football match data, converting questions to SQL queries and returning results.

Provides web search capabilities to AI assistants using the Kagi search API, enabling parallel queries and formatted results.

A Model Context Protocol server that enables AI agents to query Saagar Patel's writing, projects, and benchmark results from a static corpus, without scraping HTML.

A multi-tool AI assistant system that uses Model Context Protocol to connect language models with various tools, including math calculations and weather information.

Provides a Google search tool via the Serper API, returning structured results and a summary answer for LLMs like Claude.

An MCP server that provides targeted PostgreSQL schema access to AI agents, retrieving only relevant tables for a question and enforcing read-only access through multiple layers.

The open-source, self-organizing memory for all your AI tools. Persistent memory over MCP (remember, recall, observe): background agents extract entities, resolve conflicts, and keep cited syntheses current in an append-only, encrypted, single-tenant vault.

Enables saving project facts as they occur and retrieving only task-relevant entries when starting new work, using Jev evaluation to rank them while preserving all stored context.

Local RAG system for Claude Code with hybrid search (semantic + BM25), cross-encoder reranking, markdown-aware chunking, and 12 MCP tools. Zero external servers, pure ONNX in-process.

Enables searching and reading AVEVA Customer Support Portal knowledge base articles, including tech notes, known issues, and error-message diagnostics, to ground AI answers in support content not found in public documentation.

Enables Claude and other MCP-compatible agents to process documents, extract structured data, detect PII, and export LLM-ready datasets through natural language tool calls.

Next-gen AST codebase map, token compression (70%~85% savings), and context packaging engine for AI coding agents & IDEs.

Hardened MCP bridge to the full Ollama ecosystem — local and cloud models. 6 tools covering health, model management, chat, and generation with SSRF mitigation, singleton HTTP client, and structured error handling. Two deps, one file.

An MCP server that finds relevant xkcd comics during conversation by semantically matching the context to comic titles, alt text, and transcripts.

MCP server that converts URLs into token-minimized clean text for LLMs, providing a receipt of token and cost savings.

ContextLattice is an HTTP-first, MCP-compatible memory/context/task orchestrator that persists writes and returns fused recall from specialized stores with local-first defaults. Primary URL: https://contextlattice.io/ Install: https://contextlattice.io/installation.html Troubleshooting: https://contextlattice.io/troubleshooting.html

Enables AI assistants to answer questions about French administrative procedures for individuals, professionals and the self-employed using only official service-public.gouv.fr guides. Every answer returns verbatim official text with a citable link and last update date, and flags low-confidence results when nothing relevant is found.

Local-first memory for coding agents. Discovers the memory, instructions, and rules Claude Code, Codex, and Cursor already wrote on your machine, combines them into one canonical Markdown tree, and serves grounded, cited recall through tools like ask_memory and canonical_memory.

Provides versioned, structured memory for AI agents, allowing them to store facts, detect conflicts, and track knowledge history via a hosted SaaS platform. It enables efficient hierarchical information retrieval and semantic search while keeping token usage constant as memory scales.

Enables clients to interact with PipesHub data and functionality through MCP, including chat, search, record retrieval, directory browsing, sources, and agents.

MCP server for searching French and European law, providing natural language access to jurisprudence, consolidated legal texts, and related legal information via tools like search_decisions and search_legal_texts.

Provides AI assistants with real-time web search, reasoning, and research capabilities through Perplexity's Agent API and Search API, enabling tools for search, conversational Q&A, deep research, and advanced reasoning.

Enables semantic search and retrieval over a locally supplied copy of Lemma's documentation, providing ranked excerpts and full-text chunk access via read-only MCP tools without calling live banking APIs.

SEC EDGAR filing MCP for equity research agents: search 10-K/10-Q/8-K with CompanyFacts metrics, preview a free sample, and purchase full structured JSON via x402 USDC on Polygon. Public endpoint on xpay.tools.

Enables querying Brazilian PCDT clinical protocols from Conitec and generating concise, context-specific treatment summaries using a local LLM, with verified literal citations and links to official PDFs.

Provides fast, token-efficient search over coding agent documentation (e.g., Claude Code, Cursor) using local SQLite FTS5 indexing, with tools for searching snippets, reading pages, and grepping markdown.