To add persistent memory to Gemini CLI, register Answer Engine as an MCP server and point it at a scoped memory library. Gemini CLI stays the terminal agent. Answer Engine stores source-linked facts outside the client, so project memory can be reused from other MCP-compatible tools too.
Last updated: June 20, 2026.
Why use external memory with Gemini CLI?
Gemini CLI is terminal-first and already built for developer workflows. The Gemini CLI repository describes it as an open-source AI agent in the terminal and lists MCP support for custom integrations. Its MCP server integration docs document how MCP servers extend Gemini CLI.
External memory is useful because GEMINI.md and the current terminal session cannot hold every prior decision with source lineage. Memory should sit outside the client and return only relevant facts.
What config should you add?
Use this server shape in the Gemini CLI MCP configuration path described by the current docs:
{
"mcpServers": {
"answer-engine": {
"command": "npx",
"args": ["answer-engine-mcp"],
"env": {
"ANSWER_ENGINE_API_KEY": "ae_live_your_key_here",
"ANSWER_ENGINE_API_URL": "https://engine.answeragent.ai",
"ANSWER_ENGINE_LIBRARY": "personal-memory"
}
}
}
}The MCP introduction explains the standard. The architecture docs explain that MCP servers expose tools and resources to clients.
What should you put in Gemini CLI memory?
Use memory for durable codebase facts:
- Project setup decisions.
- Test and build commands.
- Architecture constraints.
- Issue-specific learnings.
- Prior investigation results.
- Source URLs or file paths that support a decision.
Keep transient shell output in the current context unless it explains a durable decision. This prevents memory bloat and noisy retrieval.
How do you verify the setup?
Ask Gemini CLI:
Use Answer Engine memory to find the current project test command and cite the source.The result should name the memory source or content item. If Gemini CLI answers from its prompt alone, ask it to call the Answer Engine tool explicitly. If the tool returns nothing, check the API key, library scope, and whether memory was written.
How does this compare with GEMINI.md?
GEMINI.md is useful static context. It should contain stable instructions that the agent needs at startup. It is not a write path, retrieval trace, or deletion system. Use GEMINI.md to tell Gemini CLI to call memory; use Answer Engine memory to store source-linked facts that change over time.
Read CLAUDE.md is not memory for the same boundary in Claude Code. The principle applies to GEMINI.md too.
What should you ask Gemini CLI to save?
Save facts that are durable, scoped, and sourced. A good Gemini CLI memory write names the project, the fact, and the evidence:
Save this project memory in Answer Engine: run marketing content checks with pnpm exec vitest run --config vitest.config.ts --dir tests tests/marketing. Source: repo test workflow.That style is easier to inspect than “remember the tests.” It also gives future agents enough context to decide whether the fact still applies.
Do not ask Gemini CLI to save every terminal observation. If a command failed because a server was not running, keep that in the current conversation unless it reveals a durable setup rule. If a user corrects Gemini’s assumption about where code lives, write that correction because future sessions need it.
How should you debug a missing memory?
Debug from the memory server outward:
| Check | What it proves |
|---|---|
| Search the library with the CLI | The memory exists outside Gemini CLI |
| Check the MCP server config | Gemini CLI can reach the correct server |
Confirm ANSWER_ENGINE_LIBRARY | The client is not querying the wrong scope |
| Ask Gemini to call the tool explicitly | The model is not answering from prompt context only |
If the CLI can find the memory but Gemini CLI cannot, the problem is tool configuration or instructions. If neither can find it, the problem is ingestion or write policy.
Keep one known-good memory for smoke testing. A stable fact such as the project test command makes it obvious whether Gemini CLI is calling the memory server or answering from local prompt context.