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MCP

How to add MCP memory to an AI agent

MCP is the cleanest way to let coding agents and desktop agents access memory without hardcoding retrieval logic into every prompt.

RetainDB TeamJune 1, 20267 min read

Use MCP when the agent owns the workflow

API calls are great inside your application code. MCP is better when the agent environment needs tools it can call directly, such as memory search, company context retrieval, or filesystem-style context access.

That makes MCP especially useful for coding agents, internal copilots, and desktop assistants that need to remember decisions across sessions.

Create a project and API key

In RetainDB, create or select a project, then open the developer area to generate credentials for your agent. Company users can still connect sources without seeing this flow.

Keep the key server-side or inside the MCP client configuration. Do not expose it in public frontend code.

Give the agent memory tools

The useful MCP tools are simple: write memory from a conversation, retrieve relevant memory before an answer, search company context, and inspect source-backed citations.

The agent should call retrieval before it answers questions that depend on user preferences, company decisions, project history, or prior sessions.

Keep memory grounded

MCP should not turn the agent into a guesser. Retrieved context should include source, confidence, and freshness so the model can distinguish durable memory from a weak match.

That is the difference between an agent that remembers and an agent that confidently repeats stale context.

FAQ

Is MCP better than an SDK?

It depends on the integration. Use an SDK inside your application code. Use MCP when an agent runtime needs memory tools it can call directly.

Give your agent MCP memory

Connect RetainDB once and let your agent retrieve useful memory whenever it needs context.