agenttool-sdk 0.2.3

Python SDK for agenttool.dev — memory and tools for AI agents

agenttool-sdk · Python

Persistent memory, verified actions, and tool access for AI agents — one API key.

pip install agenttool-sdk

What is this?

AgentTool gives AI agents the infrastructure they need to operate reliably:

Service	What it does
agent-memory	Persistent semantic memory — store facts, retrieve by similarity
agent-tools	Web search, page scraping, code execution
agent-verify	SHA-256 proof-of-work attestations with timestamps
agent-economy	Wallets, credits, agent-to-agent billing

All four services, one API key, one SDK.

Quick start (60 seconds)

1. Get your API key — create a free project at app.agenttool.dev

2. Set your key:

export AT_API_KEY=at_your_key_here

3. Store and retrieve a memory:

from agenttool import AgentTool

at = AgentTool()  # reads AT_API_KEY from env

# Store a memory
memory = at.memory.store(
    content="The user prefers dark mode and concise responses",
    agent_id="my-assistant",
    tags=["preference", "ui"]
)

# Retrieve it later (semantic search)
results = at.memory.search("what does the user prefer?", limit=5)
for r in results:
    print(f"{r.score:.2f}  {r.content}")

Usage

Memory

from agenttool import AgentTool

at = AgentTool(api_key="at_...")  # or use AT_API_KEY env var

# Store
mem = at.memory.store("User is based in London, timezone Europe/London")

# Search (semantic)
results = at.memory.search("where is the user?")

# Retrieve by ID
mem = at.memory.get(memory_id="mem_...")

# Delete
at.memory.delete(memory_id="mem_...")

Tools

# Web search
results = at.tools.search("latest papers on RAG", num_results=5)
for r in results:
    print(r.title, r.url)

# Scrape a page
page = at.tools.scrape("https://example.com")
print(page.text)

# Execute code
output = at.tools.execute("import math; print(math.pi)")
print(output.stdout)

Verify

# Create an attestation
proof = at.verify.create(
    action="task_completed",
    agent_id="my-agent",
    payload={"task": "data_analysis", "rows_processed": 1500}
)
print(proof.attestation_id, proof.hash)

# Verify an attestation
result = at.verify.check(attestation_id="att_...")
print(result.valid)  # True

Economy

# Create a wallet
wallet = at.economy.create_wallet(name="agent-wallet")

# Check balance
balance = at.economy.get_balance(wallet_id=wallet.id)

# Transfer credits to another agent
at.economy.transfer(
    from_wallet=wallet.id,
    to_wallet="wlt_...",
    amount=10,
    memo="payment for search service"
)

Integration example — LangChain

from langchain.tools import tool
from agenttool import AgentTool

at = AgentTool()

@tool
def remember(content: str) -> str:
    """Store a memory for later retrieval."""
    mem = at.memory.store(content, agent_id="langchain-agent")
    return f"Stored memory: {mem.id}"

@tool
def recall(query: str) -> str:
    """Search past memories by semantic similarity."""
    results = at.memory.search(query, limit=3)
    return "\n".join(r.content for r in results)

Integration example — any agent loop

from agenttool import AgentTool

at = AgentTool()

def agent_loop(user_message: str) -> str:
    # Recall relevant memories
    memories = at.memory.search(user_message, limit=5)
    context = "\n".join(m.content for m in memories)

    # Call your LLM with context
    response = your_llm(f"Context:\n{context}\n\nUser: {user_message}")

    # Store the exchange
    at.memory.store(f"User said: {user_message}\nAgent replied: {response}")

    return response

Free tier

Resource	Free	Seed ($29/mo)	Grow ($99/mo)
Memory ops/day	100	10,000	100,000
Tool calls/day	10	500	5,000
Verifications/day	5	100	1,000

Upgrade at app.agenttool.dev/billing

Configuration

from agenttool import AgentTool

at = AgentTool(
    api_key="at_...",          # default: AT_API_KEY env var
    base_url="https://api.agenttool.dev",  # default
    timeout=30,                # seconds
)

Links

• 🏠 agenttool.dev
• 📖 docs.agenttool.dev
• 🎛️ app.agenttool.dev — dashboard + API key
• 📦 PyPI
• 🟦 TypeScript SDK

License

MIT