"mcp-pcb-emcopilot" matching MCP servers:

Enables AI coding agents to access persistent, structured product context (personas, journeys, specs, decisions, domain rules) on demand, eliminating the need to re-explain product knowledge each session.

Standardize Context, Not Intelligence. An open protocol and native MCP server for preserving, organizing, and serving structured project context (architecture, decision logs, domain rules, and roadmap) to AI coding assistants (Cursor, Claude Desktop, Antigravity) with built-in CLI verification

MCP server for context-aware memory and retrieval with hybrid search, dual-phase memory, and boundary-first security.

Provides a portable context layer for MCP clients, letting users load containers with structured context, work state, and accumulated knowledge across different AI environments. It enables persistent, cross-client context management through a single MCP endpoint.

Enables managing a personal knowledge base stored in a GitHub repository, including creating 'Today I Learned' entries, prompts, and patterns, and searching or browsing entries.

Local-first memory for AI coding agents using SQLite, enabling persistent recall of decisions, lessons, and project context without cloud or API keys.

Provides LLM access to Workflowy's API, enabling agents to create, read, update, delete, and reorganize nodes in a Workflowy outline.

Enables AI assistants to access and update personalized context data, creating persistent memory between sessions.

Enables users to record probabilistic judgments in an immutable ledger, automatically score them against outcomes, and analyze systematic biases across six classification layers. It supports natural-language interaction for logging predictions, checking randomness, and auditing data integrity while avoiding advice or replacing user judgment.

Provides a shared long-term memory across any LLM via MCP, enabling semantic recall, session save/reload, and multimedia memory management with local embeddings and private storage.