weaver-kernel 0.4.0

Capability-based security kernel for AI agents operating in large tool ecosystems

agent-kernel

A capability-based security kernel for AI agents operating in large tool ecosystems (MCP, A2A, 1000+ tools).

30-second pitch

Modern AI agents face three hard problems when given access to hundreds or thousands of tools:

1. Context blowup — raw tool output floods the LLM context window.
2. Tool-space interference — agents accidentally invoke the wrong tool or escalate privileges.
3. No audit trail — there's no record of what ran, when, and why.

agent-kernel solves all three with a thin, composable layer that sits above your tool execution layer:

• Capability Tokens — HMAC-signed, time-bounded, principal-scoped. No token → no execution.
• Policy Engine — READ/WRITE/DESTRUCTIVE safety classes + PII/PCI sensitivity handling.
• Context Firewall — raw driver output is never returned to the LLM; always a bounded Frame.
• Audit Trail — every invocation creates an ActionTrace retrievable via kernel.explain().

Architecture

graph LR
    LLM["LLM / Agent"] -->|goal| K["Kernel"]
    K -->|search| REG["Registry"]
    K -->|evaluate| POL["Policy Engine"]
    K -->|sign| TOK["HMAC Token"]
    K -->|route| DRV["Driver (MCP/HTTP/Memory)"]
    DRV -->|RawResult| FW["Context Firewall"]
    FW -->|Frame| LLM
    K -->|record| AUD["Audit Trace"]

Quickstart

pip install weaver-kernel

Note: The PyPI package is weaver-kernel (Weaver ecosystem), but the Python import remains agent_kernel.

import asyncio, os
os.environ["AGENT_KERNEL_SECRET"] = "my-secret"

from agent_kernel import (
    Capability, CapabilityRegistry, HMACTokenProvider,
    InMemoryDriver, Kernel, Principal, SafetyClass, StaticRouter,
)
from agent_kernel.drivers.base import ExecutionContext
from agent_kernel.models import CapabilityRequest

# 1. Register a capability
registry = CapabilityRegistry()
registry.register(Capability(
    capability_id="tasks.list",
    name="List Tasks",
    description="List all tasks",
    safety_class=SafetyClass.READ,
    tags=["tasks", "list"],
))

# 2. Wire up a driver
driver = InMemoryDriver()
driver.register_handler("tasks.list", lambda ctx: [{"id": 1, "title": "Buy milk"}])

# 3. Build the kernel
kernel = Kernel(registry=registry, router=StaticRouter(routes={"tasks.list": ["memory"]}))
kernel.register_driver(driver)

async def main():
    principal = Principal(principal_id="alice", roles=["reader"])

    # 4. Discover → grant → invoke → expand → explain
    token = kernel.get_token(
        CapabilityRequest(capability_id="tasks.list", goal="list tasks"),
        principal, justification="",
    )
    frame = await kernel.invoke(token, principal=principal, args={})
    print(frame.facts)           # ['Total rows: 1', 'Top keys: id, title', ...]
    print(frame.handle)          # Handle(handle_id='...', ...)

    expanded = kernel.expand(frame.handle, query={"limit": 1, "fields": ["title"]})
    print(expanded.table_preview)  # [{'title': 'Buy milk'}]

    trace = kernel.explain(frame.action_id)
    print(trace.driver_id)       # 'memory'

asyncio.run(main())

Where it fits

┌─────────────────────────────────────────────┐
│             LLM / Agent loop                │
├─────────────────────────────────────────────┤
│  agent-kernel  ← you are here               │
│  (registry · policy · tokens · firewall)    │
├────────────────┬────────────────────────────┤
│  contextweaver │  tool execution layer       │
│  (context      │  (MCP · HTTP · A2A ·        │
│   compilation) │   internal APIs)            │
└────────────────┴────────────────────────────┘

agent-kernel sits above contextweaver (context compilation) and above raw tool execution. It provides the authorization, execution, and audit layer.

Security disclaimers

v0.1 is not production-hardened for real authentication.

• HMAC tokens are tamper-evident (SHA-256) but not encrypted. Do not put sensitive data in token fields.
• Set AGENT_KERNEL_SECRET to a strong random value in production. If unset, a random dev secret is generated per-process with a warning.
• PII redaction is heuristic (regex). It is not a substitute for proper data governance.
• See docs/security.md for the full threat model.

Documentation

• Architecture
• Security model
• Integrations (MCP, HTTPDriver)
• Designing capabilities
• Context Firewall

Development

git clone https://github.com/dgenio/agent-kernel
cd agent-kernel
pip install -e ".[dev]"
make ci      # fmt + lint + type + test + examples

License

Apache-2.0 — see LICENSE.