"Chemistry information or resources" matching MCP servers:

LLM routing proxy that cuts API costs 60-90% by auto-selecting the cheapest capable model across OpenAI, Anthropic, and Google. Provides stats, config, and model comparison tools via MCP.

An MCP server that implements Retrieval-Augmented Generation to efficiently retrieve and process important information from various sources, providing accurate and contextually relevant responses.

Lets AI agents search and read a folder of Markdown documentation at query time, exposing heading-level search, whole-page or section retrieval, and page listing as tools and resources over stdio or Streamable HTTP. Can run as a CLI, a hosted endpoint, or a library inside an existing Node or Next.js site.

Give your AI agents access to 8,500+ community curated awesome lists with over 1 million curated resources.

Description: Persistent memory for AI agents with rollback, audit trails, semantic search, and knowledge graph. Zero-config local SQLite or cloud API. 23 tools, 6 resources, 3 prompts.

An MCP server that retrieves contextual information from company resources and surfaces it to coding agents as rules, reasoning, skills, and commands.

Enables AI agents to record, recall, correct, and forget evidence-backed factual claims with temporal history, while explaining whether remembered information is current, historical, or contested.

Enables MCP clients to retrieve authoritative AI Square documentation, API references, SDK examples, guides, and troubleshooting information through citation-safe hybrid search and static resources.

Enables web search functionality through Perplexity AI's API with time-based filtering options. Allows users to search the web for recent information within specified time periods (day, week, month, or year).

Enables XTend developers and agents to search and retrieve canonical XTend documentation, recipes, and kit resources through read-only MCP tools, resources, and prompts served over stateless HTTP.

An MCP server that exposes the llms.txt file and its referenced local or external resources from a project root to provide context for AI models. It automatically parses documentation links and URLs to make them accessible as additional MCP resources.

Gives AI agents access to a persistent document workspace, letting them search, read, and update notes, guides, and project documentation across a full catalog of tools, prompts, and resources. It connects either to the hosted Cloud endpoint over Streamable HTTP with OAuth or API-key auth, or to a self-hosted instance through a stdio bridge.

Enables semantic search over Omarchy, Arch Linux, and Hyprland documentation, allowing users to query configuration and usage information via natural language in Cursor, OpenCode, or Claude Code.

Enables querying and browsing educational resources from AMB Nostr relays — cross-content full-text search, passage retrieval with citations, filtering by publisher, subject, level or type, SKOS vocabulary lookup, calendar event search, and URL-to-form-prefill metadata extraction. It also supports signing and publishing Nostr events (including AMB educational resources) via NIP-46 remote signing, with stdio, HTTP and ContextVM transports.

Enables AI agents to search, read, and update persistent workspace knowledge through 22 focused tools, prompts, and resources, using either a hosted endpoint or a self-hosted stdio bridge.

Enables AI assistants to search and retrieve stored open-source information through read-only MCP tools, including evidence retrieval by document or snapshot ID with byte-integrity verification.

Enables AI agents to search, read, and update persistent knowledge bases through 22 MCP tools, prompts, and resources, connecting to either a hosted endpoint or a self-hosted API.

Enables AI agents to access, search, read, and update a persistent document knowledge base through focused tools, prompts, and resources, with workspace- and category-scoped permissions for hosted or self-hosted deployments.

An MCP server that connects to SCIM 2.0 APIs, enabling MCP clients to manage SCIM resources using natural language.

A toolkit for building Model Context Protocol servers and clients that provide standardized context for LLMs, allowing applications to expose resources, tools, and prompts through stdio or Streamable HTTP transports.