Runtime Tool Injection

When you use build_agent(servers=...), MCP tools are discovered at startup. For the default ReAct pattern, these tools are automatically available. For custom graphs, you control which nodes get tools.

How It Works

1. build_agent() discovers tools from MCP servers
2. Tools are converted to LangChain BaseTool instances
3. The engine collects all tools and passes them via config["_engine_tools"]
4. Nodes with inject_tools=True receive all discovered tools at runtime
5. Injected tools merge with any explicitly configured tools (no duplicates)

Usage

from promptise.engine import PromptGraph, PromptNode

graph = PromptGraph("my-agent")

# This node gets ALL MCP tools at runtime
graph.add_node(PromptNode("search",
    instructions="Search for information.",
    inject_tools=True,
))

# This node gets NO tools (pure reasoning)
graph.add_node(PromptNode("think",
    instructions="Analyze the results.",
    inject_tools=False,
))

# This node gets ONLY its explicit tools + MCP tools
graph.add_node(PromptNode("enhanced",
    tools=[my_custom_calculator],
    inject_tools=True,   # MCP tools ALSO added
))

graph.always("search", "think")
graph.always("think", "__end__")
graph.set_entry("search")

agent = await build_agent(
    model="openai:gpt-5-mini",
    servers={"tools": HTTPServerSpec(url="http://localhost:8000/mcp")},
    pattern=graph,
)

When to Use

Scenario	inject_tools	Why
Tool-calling node	True	Needs MCP tools to do work
Pure reasoning	False	No tools — just thinking
Routing decision	False	Lightweight, no tool overhead
Guard/validation	False	No LLM call, no tools needed
Mixed (custom + MCP)	True + explicit tools	Both available