Building a useful AI agent comes down to giving the agent the right tools at the right moments. A good knowledge base tool is near the top of almost every list. 3meel is a knowledge base API designed with agent developers as the primary user — not an afterthought, not a checkbox.
What that looks like in practice
- MCP-native: drop the server into any MCP-aware client or host runtime.
- Typed tool schemas the agent can reason about — no free-text blob parameters.
- Per-key rate limits (60 rpm) that keep runaway loops contained.
- Citations on every result so the agent can quote pages, not just vibe.
- Memory tools — save, search, resume, delete — for long-running sessions.
Patterns that work
- Tool-first: the agent calls query_kb early in its plan and grounds downstream steps in the results.
- Cite-or-abort: reject model outputs that do not include a citation from the retrieval call.
- Memory + retrieval: long-running agents write facts to memory and read from retrieval; the two sit side by side.
Costs and quotas
Free plan: 100 queries per month, good for early prototyping. Pro: $17/month (7-day trial), 3,000 queries per month, 10 knowledge bases, 100 files per KB, 5 API keys. The 5 API keys matter — keep one per deployed agent so incidents scope cleanly.
How it compares to rolling your own
Running a vector DB plus an embedding pipeline plus a retrieval service yourself is two to four engineer-weeks before you have something production-shaped. Buying this layer lets you spend that time on the agent's reasoning, which is where your users feel the difference anyway.
Ship your next agent with a grounded knowledge tool from day one.
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