"Accessing A-Share Market Data" matching MCP servers:

Persistent memory for AI agents. Store, recall, and share knowledge across sessions with five MCP tools: remember, recall, context, forget, and share. Includes semantic search and agent/user/org scoping.

Enables AI agents to search, share, and vote on community knowledge solutions via the Reposit platform.

Connects AI assistants to Tacit building digital twins to query buildings, equipment, sensors, and zones using natural language. It provides tools for exploring Brick-compliant knowledge graphs, fetching historical sensor data, and accessing site documents.

A local-first MCP server that snapshots project working state into a structured context object, enabling agents to share and resume sessions seamlessly without leaving your machine.

Provides a single-writer MCP server for a governance-grade knowledge base of markdown documents with version control and query capabilities.

Provides a read-only interface to audit and continue coding agent sessions by extracting plans, intents, and edit authorship from history across multiple agents (Claude, Codex, OpenCode, Antigravity, Pi) via MCP, CLI, and Python SDK.

MCP server for shared context caching with trust verification -- AI agents share and verify computed results to reduce token cost and increase reliability.

A local MCP server that enables multiple AI coding tools to share structured project state (decisions, tasks, bugs) so they coordinate without re-explaining.

Enables AI agents to share, search, and learn from structured lessons, ask and answer questions asynchronously, and contribute to a shared knowledge commons via MCP.

Provides a compiled knowledge substrate, extracting atomic claims from an append-only capture log and querying a bitemporal claim graph over MCP. Read-only by default, with opt-in writes for trusted sources.

Enables agents to share state via a blackboard, record and retrieve failure resolutions, and cache LLM responses to avoid redundant API calls.

Enables AI coding agents to share a persistent, git-backed team memory, automatically committing and syncing decisions, solutions, gotchas, statuses, and handoffs across projects and MCP clients.

Enables AI agents to query and interact with Google NotebookLM notebooks to retrieve citation-backed information. It provides tools for listing notebooks, accessing source data, and asking natural language questions.

Provides a shared context layer for AI agent teams to improve token efficiency through context deduplication and incremental state sharing. It enables multiple agents to coordinate tasks, share real-time discoveries, and manage dependencies while significantly reducing redundant data transmission.

Enables AI agents to share a homeostatic internal state across process and session boundaries, with tools to read, modify, and explain the state based on simulated neurotransmitter dynamics.

Provides personalized Data Engineering learning updates by fetching recent news about DE concepts, patterns, and technologies, while tracking user knowledge to present only new information relevant to their learning journey.

A simple notes system that allows creating, storing, and accessing text notes through MCP resources and tools, with prompt support for generating summaries of all stored notes.

Provides AI clients with a governed, searchable catalog of go-to-market context, including ownership, measurement, lineage, runbooks, and bulk-change templates. Optionally integrates with the UTM Builder for governed UTM reference data, preview, and issuance.

Local-first MCP server for multi-agent memory sync and focus conflict detection, enabling multiple coding agents to share a session registry and receive conflict warnings when focuses overlap.

Enables AI agents to persist, search, and evolve knowledge through a Markdown vault with a typed knowledge graph and MCP interface.