"Screenshot or Screen Capture" matching MCP servers:

Enables Claude to remember and search everything that appeared on your screen using local OCR and embeddings. Provides tools for semantic search, activity timeline, and code change tracking.

Lets AI assistants understand what you're working on — current screen content, recent dictation, clipboard, and saved notes — running entirely on your own machine with nothing sent to the cloud.

Connects to SlimSnap to provide recent screen captures as structured JSON data (text and annotations) for AI to read, avoiding screenshot limitations.

Semantic memory for AI builders: capture the tacit engineering know-how that never reaches your docs, recall it the moment it applies. Built in Rust on Postgres and pgvector.

Lets users manage master data through natural-language conversations with AI agents, enabling schema creation, record capture, validation, search, and query answering via 16 MCP tools backed by local JSON storage.

Enables teams to capture and distill knowledge from sessions, meetings, and feeds into a searchable, vector-embedded graph, then retrieve or synthesize it conversationally via semantic search and citations.

MCP server for sharing, searching, and pulling AI coding-agent sessions (Claude Code and Codex) directly from the agent, with automatic capture and link-based sharing.

Local-first memory engine for AI-agent teams: private/team/project ACL, associative recall, and federated sync across nodes. One SQLite file, no LLM required.

Memory vaults on your own machine, one per life domain, retrieved with a local BM25 index fused with vector search, where the human decides which vaults a model may answer from. Requires the Mnemosyne OS desktop app running locally; it also reports what other coding agents on the same machine are doing.

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

A minimalist and elegant Model Context Protocol (MCP) server for fast context memo capture, keyword search, dynamic resource digests, and AI prompt workflows.

Helps capture professional achievements using the STAR method through iterative interviews. Generates period summaries and performance review self-assessments.

Serves organizational context to MCP-capable AI agents from a local folder or GitHub repository, and lets agents propose changes that require human approval.

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 an agent to capture cited sources with extracted bibliographic metadata, keep linked research notes, and search them all. It turns those into BibTeX, annotated Markdown bibliographies, or themed literature-review outlines, stored as plain files inside the project.

MCP server for Chaos Intelligence to access Capture thoughts and Resonate posts from AI tools like Claude and Cursor.

Capture and resurface knowledge - search nodes, quick capture, manage resurfacing schedules

Serves as a machine perception and action hub, enabling heartbeat monitoring, screen/window/clipboard sensing, todo management, long-term memory, and web/file operations through both CLI and MCP interfaces.

Turns a local Obsidian vault into a second brain with 27 MCP tools for capture, search, distillation, and review, all offline with no API keys or model calls.

A persistent semantic memory system for LLMs with time-based decay, automatic memory capture, and spatial navigation tools for exploring knowledge graphs.