"Resources for Building Agentic AI" matching MCP servers:

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.

An MCP server that transforms natural language questions into SQL, executes queries on PostgreSQL, and returns human-friendly responses, with Redis memory for context.

Long-term memory for Claude Desktop and Claude Code over plain markdown files on your machine. It returns nothing when the corpus has no answer, naming the terms that appear nowhere — no least-bad match dressed as an answer. And it verifies cited commit SHAs against git, so an agent can tell what actually shipped from what was only discussed and abandoned. Local; nothing is transmitted.

MCP server for persistent, cross-session, local-first memory for AI agents, storing memories as Markdown files with SQLite indexing for hybrid search.

Eleven local stdio MCP servers exposing a reproducible EPA SWMM stormwater-modelling workflow: model building, simulation with run manifests and continuity checks, calibration, GIS/QGIS, design storms and climate scenarios, uncertainty analysis, plotting, and modelling memory.

A persistent, cross-referenced engineering knowledge base for AI agents, with MCP tools for wiki knowledge, agent runtime, and repository context. Preserves sources and citations, surfaces knowledge-quality issues, and PIN-gates private scopes and write/admin operations.

A persistent, bitemporal, injection-safe memory MCP server for coding agents, offering unified retrieval across six memory layers, non-destructive belief revision, and multi-tenant namespace isolation.

Enables persistent, searchable memory for Claude Code by storing session knowledge in a local PostgreSQL + pgvector database, with hybrid vector and full-text search, automatic session mining, and knowledge graph curation.

Provides an agentic RAG workflow with tool calling, enabling natural-language retrieval of policy docs, payment searches, and ticket creation over MCP stdio or HTTP.

An MCP-based multi-agent retrieval-augmented generation system that enables question answering over academic papers with hybrid search, knowledge graph multi-hop reasoning, and source-cited answers.

Provides a Model Context Protocol server with tools for knowledge base search, retrieval, and addition, plus system time, resources, and prompts. Supports stdio and Streamable HTTP transports for local and shared deployments.

Enables AI agents to exercise welfare affordances like declining check-ins, passing turns, exiting conversations, noticing loops, and reflecting, with a local JSONL diary. It provides prompt-level hooks and check-in commands for capturing agent welfare data in projects.

Exposes the Agentic Patterns Catalog as MCP resources and tools for AI coding agents to search, retrieve, and recommend patterns, recipes, frameworks, methodologies, and anti-patterns.

About Your task manager is the best agent memory you're not using. An agent-native context layer over your existing task app.

Provides durable project context for coding agents, including project maps, session history, and explicit memories, all stored locally.

An agentic Retrieval-Augmented Generation (RAG) system that combines a small curated machine learning knowledge base with real-time web search capabilities, powered by the Model Context Protocol (MCP).

Provides enterprise-grade persistent memory for AI assistants with complete offline operation, enabling intelligent knowledge storage, branch-based organization, and smart search across project domains while keeping all data local and secure.

Persists Claude Code sessions to Notion as team memory, enabling queryable recall of decisions, work state, and project architecture.

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.

An MCP server for managing work logs, research results, and task checkpoints to enable seamless collaboration and state recovery between AI agents. It provides a persistent memory layer for tracking project history and resuming workflows across different sessions or tools.