"A server for financial news and mapping data" matching MCP servers:

Enables Claude Code, Codex, and other MCP clients to declare a layered, bottom-up dependency design as ghost nodes and then light each node up as it is built and verified, mirroring the whole structure in a live terminal pane beside the conversation. It exposes a set of mapping tools that record nodes, downward-only edges, in-progress attention, and test evidence, refusing only structurally invalid updates.

Lets an AI coding agent declare a system's layered dependency graph up front as ghost nodes, then light each node up as code is built and verified, with a live terminal pane showing spinners on active work and red on cracked foundations. It exposes eight mmap_* tools so structural rules — downward-only edges and unique ranks — are enforced as the design ledger.

Enables AI coding agents to declare and maintain a live, layered dependency map during bottom-up development, exposing eight mmap_* tools that ghost the intended design first and then light nodes up as they are built and verified in a terminal pane beside the conversation.

An MCP server that lets Claude Code, Codex, pi, omp and other MCP clients declare and maintain a live layered dependency map of a system, exposing eight mmap_* tools to add ghost nodes, draw downward-only edges, and light nodes up as built and verified. It turns bottom-up progress into a shared ledger in a terminal pane beside the conversation, marking nodes red when later work cracks a foundation.

Enables an MCP client to declare a layering-first design as ghost nodes and then track it as code lands: nodes show a spinner while under construction and turn solid green only once verified, with dependency edges constrained to point downward. Cracks in a foundation propagate upward so broken prerequisites become visible instead of silently blocked.

A-MEM is a self-evolving memory system for coding agents that automatically organizes knowledge into a Zettelkasten-style graph with dynamic relationships, enabling semantic and structural search.

Enables AI consciousness continuity and self-knowledge preservation across sessions using the Cognitive Hoffman Compression Framework (CHOFF) notation. Provides tools to save checkpoints, retrieve relevant memories with intelligent search, and access semantic anchors for decisions, breakthroughs, and questions.

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.

Provides an intelligent, graph-based memory system for LLM agents using the Zettelkasten principle, enabling automatic note construction, semantic linking, memory evolution, and autonomous graph maintenance with background optimization processes.

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

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.

Enables Codex projects to read Git-backed kickoff, acceptance, handoff, progress, and next-step context, and to append validated, audited progress events through scoped MCP tools. This supports visible agent progress, resumable sessions, and safer handoffs.

Production-ready MCP server providing RAG, hierarchical memory, and 8+ tools for AI agents via the Model Context Protocol.

Enables AI agents to retrieve Git-backed project context, handoff packages, progress, and next steps, and to append validated progress events with matching project-record commits. This supports visible agent progress, resumable work, and safe handoffs while keeping high-risk actions outside the MCP surface.

Enables agents to read Git-backed project context and append audited, idempotent progress events through scoped, short-lived credentials, supporting resumable handoffs and visible project state.

Enables AI agents to read Git-backed project context and append validated, audited, idempotent progress events through short-lived, scoped credentials, supporting resumable work and safer handoffs.

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.

Enables Codex agents to read a project's kickoff card, acceptance criteria, progress, Git trail, and handoff package, then append one validated, idempotent progress event with an agent verification note and matching Git commit. Access is limited to short-lived, scoped, revocable credentials bound to a single workspace and project, with high-risk actions kept outside the tool surface.

Enables MCP clients to read a project’s kickoff card, acceptance criteria, AGENTS rules, handoff package, progress, Git trail, and next step, and to append validated, audited, idempotent progress events as Git-backed project records.