"Resources for Interacting with Blockchains Like Ethereum" matching MCP servers:

Enables Claude to write in your personal style by learning from your local documents. It provides statistical style context for natural language rewriting, all without any data leaving your machine.

Enables AI harnesses to maintain a persistent memory layer backed by a local SQLite file, providing MCP tools to add, search, deprecate, and synchronize facts without deleting history.

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.

Memory bank with Server as SSH support for central knowledge base

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.

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.

Enables Codex and 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 tied to project-record Git commits.

Enables agents to retrieve project context and append validated, audited progress events through scoped MCP tools, keeping project records Git-backed and handoffs resumable.

Enables AI agents to retrieve Git-backed project context—kickoff cards, acceptance criteria, handoffs, progress, and next actions—and to append validated, audited progress events under scoped credentials.

Enables Codex agents to pull a project's kickoff card, acceptance criteria, AGENTS rules, handoff package, progress, Git trail, and next step, then append a single validated, audited, idempotent progress event with a matching project-record commit. Access is scoped to one short-lived, revocable credential bound to a single workspace and project.

A bridge between MCP Host applications and mem0 cloud service, specialized for project management with capabilities to store, retrieve, and search project information within a structured format.

MCP server for Obsidian vaults, optimised for Cursor agents — safe note editing, lean tool surface, direct filesystem access.

Provides a scalable knowledge graph implementation for Model Context Protocol using Elasticsearch, enabling AI models to store and query information with advanced search capabilities, memory-like behavior, and multi-zone architecture.

Enables chat with multiple LLM providers (OpenAI and Anthropic) while maintaining persistent conversation memory. Provides extensible tool framework for various operations including echo functionality and conversation storage/retrieval.