Compare Architectures
Side-by-side: use case, requirements, latency, cost, strengths, weaknesses, failure modes, example — and when to choose each.
Workflow vs AgentSingle agent vs Multi-agentRAG vs Fine-tuningVector search vs BM25Function calling vs MCPDirect API integration vs MCPPlan-then-execute vs ReActShort-term memory vs Long-term memoryLLM-as-judge vs Deterministic evaluatorsHuman-in-the-loop vs Human-on-the-loopSupervisor vs PipelinePrompt caching vs Semantic cachingRouter vs SupervisorFramework vs No framework
| Function calling | MCP | |
|---|---|---|
| Use case | Tools that live in one application and one model integration | Tools shared across agents, clients, and teams |
| Requirements | JSON schema per tool; you write the dispatch code | MCP server process, transport (stdio / HTTP), client support |
| Latency | In-process call | Extra hop over the transport; negligible for most tools |
| Cost | Minimal | Server hosting plus tool-list tokens on every session |
| Strengths | Simplest possible path; full control | Discovery, reuse, standardized auth and lifecycle |
| Weaknesses | Every app re-implements the same integrations | Extra moving part; oversized tool lists bloat context |
| Failure modes | Schema drift between prompt and dispatcher | Untrusted server, tool poisoning, version mismatch |
| Example | A lookup_order(id) tool in your own backend | One GitHub server used by an IDE, a CLI agent, and a chatbot |
| Choose this when | Choose function calling when one app owns the tools; it is the default. | Choose MCP when the same tools must be exposed to multiple clients or built by other teams. |