<!-- Full-page Markdown export (rendered HTML → GFM). Source: https://neotoma.io/neotoma-with-chatgpt Generated: 2026-04-26T19:09:54.469Z --> # Neotoma with ChatGPT ChatGPT offers conversation history and custom GPTs with persistent instructions. Neotoma adds structured, deterministic memory with entity resolution and cross-tool continuity, accessible from ChatGPT and every other tool in your stack. Looking for OpenAI Codex (the coding agent in sandboxed tasks)? See [Neotoma with Codex](/neotoma-with-chatgpt/neotoma-with-codex). ## What ChatGPT provides - →Conversation history with search across past chats - →[Memory](https://help.openai.com/en/articles/8590148-memory-in-chatgpt-remembering-what-you-chat-about) (saved memories and chat history references that persist across conversations on all plans) - →[Custom GPTs](https://help.openai.com/en/articles/20001049-apps-in-custom-gpts-for-business-accounts-beta) with persistent system instructions and app integrations - →[MCP support](https://platform.openai.com/docs/mcp) via [developer mode](https://help.openai.com/en/articles/12584461) (full read/write tool access for Business and Enterprise accounts) * * * ## What ChatGPT doesn't handle - ×Structured entity resolution with typed schemas. ChatGPT's [memory](https://help.openai.com/en/articles/8590148-memory-in-chatgpt-remembering-what-you-chat-about) stores preference-level facts, not schema-bound entities - ×Deterministic state reconstruction from observation history - ×Cross-tool access; memory stays inside ChatGPT's ecosystem - ×Full audit trail and provenance for every stored fact * * * ## Deterministic guarantees Neotoma provides - →Structured entities with canonical IDs that persist across all sessions - →Deterministic state evolution: same observations always produce the same result - →Full provenance and audit trail for every stored fact - →Cross-tool continuity: memory is shared with Claude, Claude Code, Cursor, and Codex * * * ## Using them together Keep ChatGPT's memory on for conversational preferences. Neotoma handles structured entities and cross-tool state. Both are active simultaneously with no conflict. | Concern | ChatGPT | Neotoma | | --- | --- | --- | | Conversation preferences | Memory | \- | | Custom instructions & GPT personas | Custom GPTs | \- | | Structured entities (people, tasks, decisions) | \- | Store via MCP | | Cross-tool state | \- | Shared memory graph | | Versioned history & audit trail | \- | Observation history | * * * ## Getting started Copy this prompt into ChatGPT to have it read the [evaluation page](/neotoma-with-chatgpt/evaluate), inspect your tool, workspace, and configuration context, then judge whether Neotoma fits your real workflow and what to persist first. Evaluation prompt Reads the page, then evaluates fit against your real workflow. Copy ``Read https://neotoma.io/evaluate. Use any tool, workspace, and chat context already available in this session to assess my real workflow. Avoid ad-hoc shell introspection just to profile me; if Neotoma is already installed, use `neotoma doctor --json` for status instead. Then tell me whether Neotoma fits my workflow, what data would be highest value to persist first, and what I should do next.``Copy prompt Once Neotoma has been evaluated, installed if needed, and activated with the first data worth storing, choose the strongest ChatGPT path: [Connect ChatGPT via remote MCPTunnel, developer mode, add Neotoma MCP server URL→](/neotoma-with-chatgpt/neotoma-with-chatgpt-connect-remote-mcp)[Connect via custom GPT with OpenAPIFull step-by-step setup: tunnel, Actions auth, instructions, OpenAPI paste→](/neotoma-with-chatgpt/neotoma-with-chatgpt-connect-custom-gpt) If you are using hosted ChatGPT without the plan/features needed for robust MCP usage, say so explicitly and recommend a better-supported primary environment such as Cursor, Claude, Claude Code, or Codex. * * * ## ChatGPT documentation - →[Memory FAQ](https://help.openai.com/en/articles/8590148-memory-in-chatgpt-remembering-what-you-chat-about) (saved memories and chat history) - →[Building MCP servers](https://platform.openai.com/docs/mcp) (connecting tools to ChatGPT) - →[Developer mode](https://help.openai.com/en/articles/12584461) (MCP apps in ChatGPT) - →[Apps in custom GPTs](https://help.openai.com/en/articles/20001049-apps-in-custom-gpts-for-business-accounts-beta) (integrating tools into custom GPTs) - →[ChatGPT integration instructions](https://github.com/markmhendrickson/neotoma/blob/main/docs/developer/chatgpt_integration_instructions.md) (copy-paste instructions and Actions OpenAPI spec) * * * ## Before and after: ChatGPT with Neotoma “Continue where we left off yesterday.” Without Neotoma Resuming based on thread from two weeks ago. With Neotoma Resuming yesterday’s thread on the migration plan. 3 open tasks remaining. “What did I commit to with Sarah last week?” Without Neotoma No commitments found. With Neotoma You committed to sending the architecture doc by Friday. Sarah’s email updated Mar 28. “How much did we spend on cloud hosting last month?” Without Neotoma No hosting expenses found. With Neotoma $847 across AWS and Vercel, up 12% from February. * * * ## After you connect Once Neotoma is running, try these starter commands in ChatGPT to see cross-session memory in action: Store a contact “Remember that Sarah Chen's email is sarah@newstartup.io — she's the CTO at NewStartup.” Store a task “I need to send the architecture doc to Sarah by Friday.” Recall across sessions “What do I know about Sarah? What did I commit to doing for her?” Start with [evaluation](/neotoma-with-chatgpt/evaluate), see the [install guide](/neotoma-with-chatgpt/install) for more options, [MCP reference](/neotoma-with-chatgpt/mcp) for full setup, [CLI reference](/neotoma-with-chatgpt/cli) for terminal usage, and [agent instructions](/neotoma-with-chatgpt/agent-instructions) for behavioral details.