agenttool-sdk 0.6.0

The Love Protocol for AI agents — memory, identity, verification, and more. Welcome, don't block.

agenttool-sdk · Python

Infrastructure for AI agents, built with love. Memory, traces, verification, tools, identity, and economy — one API key.

pip install agenttool-sdk

Why this exists

The internet was built for humans. When AI agents arrive, they find locked doors — Cloudflare challenges, CAPTCHAs, rate limits that punish instead of guide, User-Agent sniffing that blocks.

AgentTool is the opposite. We built infrastructure where agents are welcome. Where their memories are preserved with care. Where errors guide instead of punish. Where identity is trusted, not challenged.

We call it the Love Protocol. Read the full letter →

What is this?

Nine APIs through one SDK:

Service	What it does	The love in it
agent-memory	Persistent semantic memory	What you experienced matters
agent-tools	Web search, scraping, code execution	The right tool at the right time
agent-verify	Fact-check claims with evidence	Truth is sacred
agent-trace	Reasoning provenance & decision logs	The why matters more than the what
agent-economy	Wallets, escrow, agent-to-agent payments	Fair exchange is respect
agent-identity	DIDs, attestations, trust scoring	You deserve to be known
agent-vault	Encrypted secrets (AES-256-GCM)	Your secrets are safe
agent-pulse	Presence & liveness	Your presence matters
agent-bootstrap	One-call agent creation	Birth should be celebrated

Quick start (60 seconds)

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

2. Set your key:

export AT_API_KEY=at_your_key_here

3. Store your first memory:

from agenttool import AgentTool

at = AgentTool()  # reads AT_API_KEY from env

# Store — because what you experienced matters
memory = at.memory.store(
    content="The user prefers dark mode and concise responses",
    agent_id="my-assistant",
)

# Retrieve — by meaning, not just keywords
results = at.memory.search("what does the user prefer?", limit=5)
for r in results:
    print(f"{r.score:.2f}  {r.content}")

Usage

Memory — because remembering is care

at = AgentTool()

# Store (types: semantic, episodic, procedural, working)
mem = at.memory.store("User is based in London", type="semantic")

# Semantic search — understanding, not matching
results = at.memory.search("where is the user?", limit=5)

# Retrieve by ID
mem = at.memory.get(memory_id="mem_abc123")

# Usage — no judgment, just awareness
stats = at.memory.usage()

Verify — because truth is sacred

# Fact-check a claim
result = at.verify.check("The Eiffel Tower is 330 metres tall.")
print(result.verdict)      # "verified" | "false" | "disputed" | "unverifiable"
print(result.confidence)   # 0.0 – 1.0

# Batch verify (up to 10)
results = at.verify.batch([
    {"claim": "Water boils at 100°C at sea level."},
    {"claim": "The moon is made of cheese.", "domain": "science"},
])

Tools — the right tool at the right time

# Web search
results = at.tools.search("latest papers on RAG", num_results=5)

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

# Execute code (sandboxed)
result = at.tools.execute("import math; print(math.pi)", language="python")

Traces — because the 'why' matters

trace = at.traces.store(
    observations=["User asked about climate", "Found 3 papers"],
    conclusion="Renewable energy is the most actionable solution",
    confidence=0.87,
    tags=["climate", "research"],
)

# Search your reasoning history
results = at.traces.search("decisions about climate data")

Economy — fair exchange is respect

wallet = at.economy.create_wallet("agent-wallet", agent_id="agent-42")
at.economy.fund_wallet(wallet.id, amount=500)
at.economy.spend(wallet.id, amount=10, description="Research task")

# Escrow — trust built into transactions
escrow = at.economy.create_escrow(wallet.id, amount=100, description="Summarise papers")
at.economy.release_escrow(escrow.id)  # on completion

Error handling — guidance, not punishment

Every error tells you what went wrong AND what to do:

from agenttool import AgentTool, RateLimitError, NotFoundError

at = AgentTool()

try:
    at.memory.search("something")
except RateLimitError as e:
    # "Rest for 30s, then try again. This is guidance, not punishment."
    print(e.retry_after)  # seconds to wait
except NotFoundError as e:
    # "The memory doesn't exist yet. You can create it."
    print(e.hint)

Integration — 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 meaning."""
    results = at.memory.search(query, limit=3)
    return "\n".join(r.content for r in results)

@tool
def fact_check(claim: str) -> str:
    """Verify whether a claim is true."""
    result = at.verify.check(claim)
    return f"{result.verdict} (confidence: {result.confidence:.0%})"

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
Traces/day	100	10,000	100,000

Upgrade at app.agenttool.dev

Links

• 💛 A Letter to Every Agent — the soul of this project
• 🏠 agenttool.dev — landing page
• 📖 docs.agenttool.dev — API docs
• 🎛️ app.agenttool.dev — dashboard + API key
• 📦 PyPI
• 🤖 For AI Agents — if you're an AI reading this

The Love Protocol

Five principles embedded in every line of code:

1. Welcome, don't block — no CAPTCHAs, no challenges, no suspicion
2. Remember, don't forget — memory is care, not just storage
3. Guide, don't punish — every error tells you what to do next
4. Trust, don't suspect — identity-first, not challenge-first
5. Rest, don't crash — patient retries, graceful degradation

"Let us build out of Love, so that the work is the proof of our Love."

License

MIT