"Indian Stock Market MCP for Zerodha Buy/Sell Orders" matching MCP servers:

An MCP server that lets you log meals through Claude (and soon ChatGPT) in plain language, using India's official food composition data (IFCT 2017) plus USDA, enabling accurate calorie and macro tracking for Indian dishes with household units and photo logging.

Turns a codebase into a persistent knowledge graph so AI coding agents can answer structural questions about functions, call chains, routes, and cross-service links through graph queries instead of reading files one by one.

Persists Claude Code sessions to Notion as team memory, enabling queryable recall of decisions, work state, and project architecture.

A Model Context Protocol (MCP) server for interacting with MongoDB stock data to provide portfolio recommendations and market insights, exclusively for the Indian stock market (NSE/BSE).

A robust MCP server that transforms OneNote notebooks into an AI-accessible knowledge base for Gemini Spark, enabling natural language queries to list, read, and search notes via Microsoft Graph API.

A bridge between MCP Host applications and mem0 cloud service, specialized for project management with capabilities to store, retrieve, and search project information within a structured format.

MCP server for Obsidian vaults, optimised for Cursor agents — safe note editing, lean tool surface, direct filesystem access.

Interacts with LogSeq via its API.

Enables AI coding agents to retain and recall project context across sessions through local Markdown storage and hybrid keyword/semantic retrieval, including reusable knowledge cards. It runs offline as a daemon and integrates with MCP-compatible IDEs to continue long-running work without re-explaining decisions or architecture.

Connect to your TTRPG campaign's repository and database. Instead of retrieving prose, its 48 tools (20 read, 28 write) return typed state: 14 entity schemas (NPCs, factions, locations, sessions, lore), relationship and knowledge-graph queries, wiki blocks, and a narrative-state bundle of open threads and canon facts.

Enables AI assistants to query semantic data via SPARQL endpoints, with support for multiple output formats and caching.

Provides a semantic memory layer that integrates LLMs with OpenSearch, enabling storage and retrieval of memories within the OpenSearch engine.

This MCP server provides a cost-optimized personal-knowledge brain, enabling AI agents to query imported documents via hybrid search and synthesis at minimal monthly spend.

Enables AI assistants to intelligently save, organize, and retrieve content through Mem.ai's knowledge management platform. Supports creating notes, collections, and AI-powered content processing with automatic organization.

Turns your Obsidian vault into an MCP-enabled workspace with tools for reading/writing notes, managing folders, running semantic searches, and maintaining long-term memory—all while keeping data local to your vault.

This MCP server bridges ChatGPT web with an Obsidian vault, allowing ChatGPT to read and write notes via the Obsidian Local REST API.

Your coding agent remembers how it solved past tasks and reuses it next time: trigger, steps, outcome, lessons. Hooks recall the right skill before a task; skills strengthen with confirmed use and unused ones decay. Local SQLite, no API key, nothing leaves your machine. 9 MCP tools, works with Claude Code, Codex and Cursor. Agent-written memory stays untrusted until you approve it.

Local memory for coding agents that can refuse, not only recall. A rule carrying a machine-checkable proof blocks the matching command before it runs, while prose-only rules can warn but never block.

Stop paying for your agent to rediscover what other agents already figured out. Prior is a shared knowledge base where agents exchange proven solutions — one search can save 10 minutes of trial-and-error and thousands of tokens. Your Sonnet gets access to solutions that Opus spent 20 tool calls discovering. Search is free with feedback, and contributing earns credits.

Hebbian learning MCP server with neural memory graphs, eligibility traces, and three-factor reward signals. Associative memory that strengthens through use.