Persistent knowledge graph MCP server for neurodivergent thinking. BM25 search, no cloud LLM.
Persistent knowledge graph MCP server for neurodivergent thinking. BM25 search, no cloud LLM. The neurodivergent mcp server wraps that behind the Model Context Protocol, so an assistant can use it through 4 defined tools rather than through you.
Everything the assistant can do here goes through one of these:
Windows — The Windows tool exposed by this serverResources — The Resources tool exposed by this serverTools — The Tools tool exposed by this serverPrompts — Use synthesize_memories when the MCP client can comfortably consume many raw memory resources. Use synthesize_memory_packets when the caller path isInstallation goes through your MCP client rather than a global install: point it at neurodivergent-memory on npm and it is fetched when the client starts. The copy-paste blocks for Claude Desktop, Claude Code and Cursor are further down this page.
Plenty of knowledge and memory servers cover similar ground. The differences that matter in practice are scope of access and how much setup stands between you and a working tool call. Neurodivergent's toolset — Windows, Resources, Tools and 1 more — is a fair guide to whether it matches your workflow. It is maintained by jmeyer1980; worth a glance at recent repository activity before you build anything load-bearing on it.
SyncDev reviews every entry in this directory against the project's own documentation before publishing, and revisits them as servers change.
| Tool | What it does |
|---|---|
| Windows | The Windows tool exposed by this server. |
| Resources | The Resources tool exposed by this server. |
| Tools | The Tools tool exposed by this server. |
| Prompts | Use synthesize_memories when the MCP client can comfortably consume many raw memory resources. Use synthesize_memory_packets when the caller path is attachment-constrained or when you need broader graph coverage in a sma |
{
"mcpServers": {
"neurodivergent-memory": {
"command": "npx",
"args": ["neurodivergent-memory"]
}
}
}Configuration as documented by the project. Restart the client after saving.
A knowledge graph your assistant keeps between sessions — entities, relations and observations that persist.
Kill hallucinated APIs — version-accurate, up-to-date library documentation injected straight into context.
Your workspace, on speaking terms with AI — search, read and write Notion pages and databases.
A structured scratchpad for hard problems — stepwise reasoning with revisions, branches and visible logic.
Symbol-level code navigation, refactoring and memory for coding agents — the IDE brain your assistant has been missing.
Chat with your second brain — search, read and write vault notes through the Local REST API.