"Fetching data from an MCP server" matching MCP servers:

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.

Author rules from policy docs, then decide: a Rete engine gives the verdict, an LLM explains why.

An MCP server that lets Claude Code recall the context of past conversations from any project on demand.

StelaSpace is an HTML-first knowledge base for the artifacts AI agents create. This MCP server lets Claude Code, Claude Desktop, and Codex publish HTML files straight from your editor — it takes a file path and uploads from disk, so even large data-heavy reports work. Free tier available.

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.

Enables an AI agent to read a writer's manuscript, story world, and timeline from ezQuill with the writer's consent and within allowed permissions.

An MCP server that allows AI assistants to search and retrieve human-curated content recommendations from Copus.

Enables keyword search, filtering, and retrieval of Claude Code memory files, reducing context overhead by fetching only relevant memories on demand.

Provides a compressed knowledge graph of the NVIDIA AI developer stack for deterministic traversal, enabling agents to answer questions about dependencies and prerequisites with minimal tokens.

An MCP server that provides AI trading agents with persistent, outcome-weighted memory to learn from historical performance and detect behavioral biases. It enables agents to automatically adjust strategies and optimize position sizing based on context-aware recall of past trade outcomes.

Enables personal knowledge management through Claude Desktop, allowing users to capture thoughts, connect ideas, and reflect on thinking changes via natural conversation.

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

Enables coding agents to retrieve project context from an AnythingLLM RAG at session start and write back human-approved durable facts via five workflow-shaped tools.

A forkable RAG project with an MCP server for VS Code/Copilot, enabling indexing and querying of knowledge from URLs, PDFs, or TeX files.

A personal digital twin MCP server that manages professional context, including skills, experience, and project learnings. It allows AI assistants to retrieve and update user preferences and career interests across different development environments.

Enables AI assistants to read and write a local-first SQLite memory vault from inside a chat — orienting on inherited context, searching and fetching past decisions and notes, wandering linked memories, and recording new ones on demand. All data stays on the user's machine, shared across local and cloud tools via MCP.

A Model Context Protocol server that enables AI models to perform real-time internet and knowledge searches through Higress, enhancing model responses with up-to-date information from Google, Bing, Arxiv, and internal knowledge bases.

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 Claude and ChatGPT to share a single study-progress database for interview prep, coursework, and spaced repetition, with per-user data isolation and server-side SM-2 scheduling for due reviews and study plans.

Captures commitments from LLM conversations into a persistent local task list shown on an edge strip, with tools to add, list, and complete tasks.