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A backend (also called a provider mode) controls how your tools are presented to the LLM. It sits between the agent and your tools, deciding what the LLM sees and how it invokes them.

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Why Backends Matter

When an LLM connects to your MCP server, it calls list_tools() to discover what’s available. The backend determines what comes back: The choice of backend directly affects:
FactorImpact
Token costMore tools in context = more tokens per request
AccuracyFewer choices = LLM picks the right tool more often
DeterminismStructured execution = more predictable outcomes
ComposabilityCode/Plan modes let the LLM chain tools in a single turn

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Available Backends

Plain

All tools exposed directly. Simple, no wrapping. Best for small APIs.

Search

Semantic search over tools. Agent discovers then calls. Best for large APIs.

Plan

Agent submits a JSON execution plan. Sequential steps with data passing. Best for workflows.

Code

Agent writes Python to call tools. Maximum efficiency. Best for complex logic.

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Configuring a Backend

from concierge import Concierge, Config, ProviderType

# Default:Plain
app = Concierge("my-server")

# Explicit
app = Concierge(
    "my-server",
    config=Config(provider_type=ProviderType.SEARCH),
)
The default is Plain. Change it by passing ProviderType.SEARCH, ProviderType.PLAN, or ProviderType.CODE.

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Comparison

BackendLLM seesContext costBest for
PlainAll tools directlyHighUnder 20 tools
Searchsearch_tools + call_toolMedium100+ tools
Planexecute_planLowMulti-step workflows
Codeexecute_codeMinimalComplex logic, iteration

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Backends + Stages

Backends work on top of stages. If you define stages, the backend only operates on the tools visible in the current stage:not all tools: 
app = Concierge(
    "my-server",
    config=Config(provider_type=ProviderType.CODE),
)

app.stages = {"browse": ["search"], "checkout": ["pay"]}
app.transitions = {"browse": ["checkout"], "checkout": []}
In the browse stage with Code mode, tools.pay() raises an error:it’s only available after transitioning to checkout.