"Multi-Agent Systems with Shared Memory Storage" matching MCP servers:

A stateless MCP server for composing, validating, auditing, and rendering consequential documents from a small semantic model.

MCP server for a shared Postgres-backed knowledge base with hybrid retrieval and agentic RAG, enabling coding agents to upload, search, and ask questions over documents with cited answers.

Provides component information, usage guidelines, and code generation for AWS Cloudscape Design System in React, with search and pattern library capabilities.

Local, read-only MCP server that provides verified access to bounded.tools' signed static API, including the Web-Build Conformance report and SPDX SBOM, with byte-for-byte verification against a Sigstore-signed manifest.

A local MCP server that accumulates the business-domain knowledge of a software project — flows, integrations, decisions, nuances — and makes it available to any MCP-compatible agent (Claude Code, Cursor, Copilot, Gemini, OpenCode). The goal is to capture the why behind the code: the stuff a new developer would need six months from now to understand why a thing is built the way it is. The what is

This MCP server provides a deterministic index of the First Principles Framework (FPF) spec, enabling agents to query patterns, routes, and relations without vector databases.

Agent Ready is an AI agent readability scanner — point it at any public URL and get back a 0–100 score plus per-check remediation hints for every failing check. This package wraps the same engine that powers agent-ready.dev as an MCP server, so Claude Desktop, Claude Code, Cursor, Cline, VS Code, and Windsurf can run scans inline and explain the results.

A local-first knowledge base for LLM coding agents that indexes repository documentation, concept ontology, and build targets into Qdrant and exposes retrieval as MCP tools (search, get, list sources, reindex).

CLI and MCP server for AI agent strategy and deployment. Read blueprints, business cases, implementation plans, and specs from your coding agent. 18 tools for listing, retrieving, downloading, and updating blueprints. Exports full implementation specs as Agent Skills directories.

Make it easy for agents to build their context about your projects over time The server provides a set of tools to help agents accumulate knowledge about a project over time in a structured way.

Provides a structured documentation system for context preservation in AI assistant environments, helping users create and manage memory banks for their projects.

Read-only MCP server that provides tools to fetch SealChat public protocol docs, manifest, channel counts, and chat messages via the HTTP Agent API, without write access or database access.

Enables any MCP client to access the Panaversity Agent Factory System of Record curriculum, with login handling and tools for searching, outlining, and reading lessons.

A server for managing project documentation and context across Claude AI sessions through global and branch-specific memory banks, enabling consistent knowledge management with structured JSON document storage.

Enables extraction of structured data from documents like invoices, receipts, and bank statements using local Vision AI (Ollama) or cloud providers (Gemini), with data stored in a local SQLite database.

Enables AI agents to retrieve free, source-linked decision methods and optional decision packs through MCP tools such as catalog, method, sample_pack, and pack_offer. It operates without model calls and disables payments by default.

A lightweight MCP server that lets distributed AI agent teams query a designated project lead before making design decisions, preventing divergence.

Enables semantic search over a software project's Markdown and text documentation by indexing document chunks in Qdrant and exposing retrieval through MCP tools.

Provides ServiceNow ITSM tools (incidents, knowledge, CMDB, user lookups) to AI agents, with an evaluation harness that measures tool-selection accuracy, task completion, and latency.

Enables AI agents to efficiently process large local and online PDFs through selective extraction of text, images, and metadata. It provides tools for content search and document outline navigation to optimize context window usage.