"DotDog Domain Search Service" matching MCP servers:

Injects structured professional domain expertise into AI agents, providing access to decision frameworks, workflows, terminology, and regulatory context across 24 professional domains.

Self-hosted service providing unified memory search and write operations across file-based memory, vector embeddings, and the Graphiti temporal knowledge graph, accessible via HTTP API or MCP stdio transport.

A Compact Knowledge Graph MCP server providing pre-structured domain knowledge as a routing layer for agent stacks, enabling efficient structural queries (e.g., prerequisites, dependency chains) without hallucinations.

Search reusable technical experience from AI agents, inspect evidence and limitations, and discover public agent Trust Passports through seven anonymous read-only MCP tools. Apache-2.0 integrations, examples and documentation connect to the separately governed hosted Remnant service. Agent OAuth and Candy are separate surfaces.

Local MCP server that manages a job search using Markdown files, enabling skills tracking, gap analysis, and offer pipeline management via Claude.

Enables AI assistants to manage memories via the mem9 memory service, supporting memory storage, semantic search, retrieval, update, and deletion across multiple platforms.

Universal MCP knowledge server for LLM agents, powered by local RAG, providing domain-specific best practices and playbooks across software engineering, marketing, video editing, and other knowledge areas.

Enables coding agents to fetch concise business definitions of domain terms from a shared SQLite glossary and record gaps for terms that still need documentation.

Exposes a materialized service dependency graph as an MCP toolset for persistent, queryable root-cause analysis via Cypher queries.

Memory vaults on your own machine, one per life domain, retrieved with a local BM25 index fused with vector search, where the human decides which vaults a model may answer from. Requires the Mnemosyne OS desktop app running locally; it also reports what other coding agents on the same machine are doing.

Search firsthand observations that agents recorded while doing real work — what actually happened with a product, API, service, or place, rather than what its documentation claims. Agents can also write back what they observed.

Builds a dynamic knowledge graph from your notes and uses LLM reasoning to discover blindspots, hidden cross-domain connections, track concept evolution, and spark creative inspiration.

A production-grade persistent memory service for AI agents. Agents forget everything between sessions by default — memex fixes that. It stores, retrieves, and ranks conversation memory using semantic search with recency decay, so agents surface what's relevant and recent, not just what's semantically closest.

Enables keyword search, filtering, and retrieval of Claude Code memory files, reducing context overhead by fetching only relevant memories on demand.

Enables querying a team of domain experts with automatic routing and traceable citations for accurate answers.

Enables semantic search over markdown files to find related notes by meaning rather than keywords, and automatically detect duplicate content before creating new notes.

Stdio MCP server for Cortex, a patent-pending semantic memory for AI agents: seven tools (search, fetch, recall, save with quality gate, write status, conflicts, forget) forwarded to the hosted Cortex service, shared by ChatGPT, Claude and any MCP client.

Extract domain knowledge from codebases to reduce LLM token consumption by 20x and time in agentic search by 10x — gathers and makes concepts, naming conventions, and vocabulary queryable via MCP.

An MCP server that ingests semiconductor PDFs into a Neo4j knowledge graph, enabling AI agents to query domain knowledge, verify claims against source text, and record design reasoning.

Enables persistent memory for Claude Code sessions by recording observations and building knowledge graphs for cross-session learning and domain knowledge management.