"Bose" matching MCP servers:

Provides 5 quantum physics simulation tools for AMO (Atomic, Molecular and Optical) physics, including two-level atom dynamics, Rabi oscillations, Bose-Einstein condensates, absorption spectra, and cavity QED simulations.

MCP server providing live Bank of England data including base rate, IADB statistical series, and MPC meeting schedule.

Enables AI assistants to search, retrieve, and browse Markdown documentation in a local folder, then answer questions with cited sources.

Provides search and retrieval of Hacker Public Radio episodes, transcripts, hosts, and series via MCP tools and resources, with fuzzy matching and flexible transcript search.

Enables Claude to look up live Bombay Stock Exchange data by scrip code, including quotes and ratios, market depth, peer comparisons, quarterly P&L with derived EBITDA and margins, corporate announcements with PDF links, and scrip search. It fetches from BSE's public endpoints so users can ask natural-language questions about Indian listed companies.

A knowledge base MCP server that aggregates team knowledge from multiple sources into Postgres. It provides hybrid search (full-text + vector + RRF) via MCP tools, and enables direct recording of decisions, learnings, and pitfalls.

Exposes a knowledge base to LLM clients through tools, resources, and prompts.

Provides MCP tools for AI assistants to retrieve compact daily futures data packets, submit manual market data, run whitelisted crawlers, search research summaries, and save/read historical reports on demand for caustic soda, PVC, and coking coal futures.

Read-only MCP server for precise lookup, search, and versioned retrieval of OWASP testing guides (WSTG, MASTG, ISTG, AITG) with full provenance on every result.

A modular, extensible Model Context Protocol server framework designed for Claude Desktop that uses convention-based automatic module discovery to easily extend AI application functionality without modifying core code.

A TypeScript-based template for rapidly developing MCP servers with modular tool architecture, built-in validation using Zod schemas, and comprehensive error handling.

Enables AI agents to share a persistent, self-improving memory by ingesting, classifying, synthesizing, and retrieving knowledge from sources like Obsidian vaults, code, and transcripts through MCP and REST APIs. Provides token-optimized, tiered retrieval with full-text and semantic search so every agent session builds on accumulated context.

Enables AI agents to capture, classify, synthesize, and retrieve persistent shared knowledge from sources such as Obsidian, code, transcripts, bookmarks, and sessions. It provides token-efficient search, context briefings, and tiered memory through MCP and REST APIs.

Enables AI agents to search Spain's consolidated legislation by title, inspect any statute's metadata and article table of contents, and read every historical version of a chosen article. Also retrieves the daily table of contents of the Spanish state gazette, grouped by section and issuing department, via the Agencia Estatal Boletín Oficial del Estado open-data API.

Enables AI agents to share a persistent, self-learning memory by ingesting and classifying knowledge from Obsidian, code, transcripts, bookmarks, and terminal sessions, then retrieving token-optimized context through MCP and REST APIs.

A cross-project knowledge base MCP server supporting three-layer search (text matching, TF-IDF, and semantic vectors) with a Web UI for management.

Enables AI agents to share persistent memory by capturing, classifying, synthesizing, and retrieving knowledge through token-optimized, three-tier retrieval with hybrid keyword and semantic search. Supports bidirectional Obsidian sync, session and bug-fix capture, and a self-learning loop that compounds context across sessions.

Gives AI agents persistent, shared memory by ingesting notes, code, transcripts, and session captures, then serving token-optimized context and hybrid keyword/semantic search over MCP and REST. Agents can classify, promote, and synthesize stored material so each session builds on prior work instead of starting from zero.

Enables AI agents and clients to capture, classify, synthesize, and retrieve persistent knowledge from multiple sources through MCP and REST APIs, with tiered memory and token-optimized context.

Gives AI agents a shared persistent memory by ingesting Obsidian vaults, code, transcripts, web clips, and session or bug-fix captures, then serving token-optimized context briefings, keyword and semantic search, and cross-source synthesis. Enables multiple agents to read and write the same growing knowledge base so each session builds on the last.