"Payload CMS" matching MCP servers:

Enables any AI coding agent to instantly find and resume sessions created in another agent. It indexes sessions from multiple harnesses locally and injects a compact, ready-to-resume payload without using LLM tokens.

Gives AI agents a persistent vector memory by embedding text with Ollama and storing it in Qdrant, so they can save, batch-save, semantically search with payload filters, and delete memories across collections.

Persistent, local, cross-IDE memory for AI agents — markdown source of truth, LanceDB-powered semantic search, zero cloud dependency

Persistent memory server for CMS Combine lessons, enabling saving and searching confirmed error-cause-fix chains across sessions and users.

Exposes codebase memory as native tools for AI agents, enabling queries, feature tracing, impact analysis, and alignment verification.

Enables passive reconstruction of an application's HTTP endpoints, WebSocket/event surfaces, payload schemas, and process architecture purely by observing labeled traffic, logs, and process metadata — never by sending requests to the target. Findings carry evidence levels and confidence, and can be exported as OpenAPI, AsyncAPI, JSON Schema, protocol catalogs, architecture maps, and candidate MCP capability surfaces.

Codebase Memory for pi. Provides cbm_* tools that answer structural questions about a codebase (symbol search, call chains, architecture, git change blast radius, and more) by querying a local tree-sitter knowledge graph, avoiding slow grep/read fallbacks.

Exposes the Integrated Memory System (IMS) capabilities, including session management, memory storage, and RAG-based context search, via the Model Context Protocol. It allows MCP-aware clients to interact with IMS backends to maintain long-term memory and context across sessions.

Provides personalized CSS learning updates by tracking known concepts in memory, fetching latest CSS news via Perplexity, and guiding users through new CSS features they haven't learned yet.

MCP server for Context Studio, a file-based CMS for governed marketing documents and searchable collections, enabling retrieval and management of AI context via tools like scopes, document reads, and collection search.

MCP server that gives AI agents human-like persistent memory, with auto-encoding, proactive recall, and memory rooms for cross-agent context.

A credential-free MCP server that turns a Substack publication's public RSS archive and official analytics snapshots into a durable, queryable local SQLite ledger. It provides 12 MCP tools for browsing posts, tracking versions, recording metric snapshots, and analyzing content patterns.

A local MCP server enabling hybrid search over documents, memory, and knowledge graphs for retrieval-augmented generation, with tools for SQLite, semantic memory, and entity-relationship queries.

Enables LLMs to perform structured, verifiable knowledge operations using the Canonical Knowledge Structure (CKS) ecosystem, including validation, querying, comparison, evolution, and derivation of knowledge.

Enables interaction with the Innovaas Knowledge Management System through MCP, providing multi-modal search, RAG-powered chat with intelligent token management, and document access.

Unifies 7,283+ detection rules from Sigma, Splunk ESCU, Elastic, and KQL into a single queryable interface via MCP, with a web dashboard and autonomous agent pipeline for detection engineering.

Enables natural-language semantic search over a fully local knowledge base, keeping embeddings, storage, and retrieval on the machine.

Enables querying MaxKB knowledge bases through MCP, supporting vector, hybrid, and full-text retrieval of relevant segments, as well as listing knowledge bases, documents, and workspaces.

A personal MCP server for managing a folder of markdown notes. It provides tools to search and list notes, resources to access individual notes, and a prompt for weekly summaries.