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A protocol for autonomous LLM agents to navigate complex toolsets via semantic landmarks.

Project description

Elemm: The Landmark Manifest Protocol

PyPI version License Python versions

The Infrastructure for the Agentic Web.

Elemm is the Landmark Manifest Protocol, a next-generation communication framework designed to transform how autonomous LLM agents interact with the digital world. Instead of static tool definitions, Elemm provides a dynamic, manifest-driven architecture that enables agents to discover, navigate, and execute complex workflows across distributed APIs with unprecedented efficiency.


The Vision: Agentic Web

In the Agentic Web, every API is a "Landmark". Agents no longer need massive, hardcoded system prompts to understand a service. They discover capabilities on-the-fly via a standardized manifest, just like a human navigates a website.

  • Unified Discovery: Every Elemm-compliant server exposes its structure at /.well-known/elemm-manifest.md.
  • Zero System Prompt: By providing rich semantic landmarks and manifest-driven discovery, you can eliminate thousands of tokens from your system prompts. The protocol is the documentation.
  • One MCP Server, Infinite APIs: Build a single Dynamic Gateway (MCP server) that connects to dozens of independent Elemm-powered microservices. The gateway discovers and loads landmarks on-the-fly, allowing you to scale your agent's capabilities without ever restarting your main infrastructure or modifying the agent's core configuration.

The Philosophy: Decoupling Intelligence

Elemm is more than just a protocol; it's a shift toward Decentralized Intelligence. In the traditional SaaS model, providers often bundle their APIs with expensive, centralized LLM interfaces. Elemm decouples the "Body" (the API) from the "Brain" (the Agent).

Bring Your Own Agent (BYOA)

With Elemm, API providers only define the Landmarks and Manifests. The user brings their own autonomous agent to the platform. This shifts the computational burden and cost of "reasoning" to the edge—the user's own system.

Sustainability & Efficiency

By eliminating the need for massive, repetitive system prompts and context-heavy tool injections, Elemm significantly reduces the global token footprint of AI interactions.

  • Lower Latency: No more waiting for centralized "gatekeeper" models to process 20k tokens of documentation.
  • Reduced CO2 & Energy: Fewer tokens mean less GPU compute time, directly translating into a lower carbon footprint for every autonomous task.
  • Cost Sovereignty: Providers save on LLM hosting and token costs, while users get the freedom to choose the model that best fits their task and budget.

Core Advantages

Standard protocols like MCP often struggle with large-scale toolsets. Elemm provides a structural solution:

  • Efficient Discovery: Agents only see a high-level manifest, loading detailed tool schemas only when needed (on-demand inspection).
  • Atomic Sequencing: Execute multiple tool calls in a single LLM turn with native variable piping ($step0.id).
  • SmartRepair Engine: Built-in error handling that provides agents with actionable remedies instead of cryptic stack traces.
  • Token Economy: Reduces input tokens by up to 90% in complex forensic and administrative scenarios.

Documentation


Quick Start

1. Install

pip install elemm[fastapi]  # Includes web server support

2. Create a Landmark Server

Elemm uses a decorator-based approach to turn standard Python functions into high-performance landmarks.

from elemm import ElemmGateway
from pydantic import BaseModel

gateway = ElemmGateway(name="SystemControl")

class SecurityRequest(BaseModel):
    node_id: str
    urgent: bool = False

@gateway.action(landmark="Security")
async def quarantine_node(request: SecurityRequest):
    """Quarantines a compromised server node."""
    return {"status": "success", "node": request.node_id}

if __name__ == "__main__":
    # Runs an Elemm-compliant API server
    gateway.run(port=8000)

Advanced Usage

  • Pydantic Discovery: Elemm automatically generates schemas from Pydantic models.
  • Raw Integration: Access the manifest as a dictionary via gateway.manager.get_manifest_dict() for custom LLM wrappers.
  • Self-Healing: The SmartRepair engine provides agents with actionable remedies (e.g., correct parameter names) when errors occur.

3. Connect to an Agent

Use the provided MCP bridge to connect your Elemm server to any MCP-compatible agent (e.g. Claude Desktop):

"elemm": {
  "command": "python3",
  "args": ["-m", "elemm.integrations.mcp_bridge", "http://localhost:8000"]
}

License

Copyright (C) 2026 Marc Stöcker. GPLv3 License. See LICENSE for details.

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