tool-development-guide

A coding guide for adding tools to the Atlan MCP server, a service that lets AI applications call defined tools. It describes where to put the main function, how to register it, and how to handle types, logging, and errors.

In plain words
What is it for?
Use it when building Atlan server tools in Python, registering them with MCP, and adding basic error handling and logging.
Why use it?
It gives developers a consistent structure for implementing and exposing new Atlan tools.

Cursor rule for Cursor

Install

Getting it into your agent

One page per mod, every tool's command on it. A separate URL per tool would split the same page into five that compete with each other.

agentmods
npx agentmods add rules/atlanhq/agent-toolkit/tool-development-guide
Clone the repo
git clone --depth 1 https://github.com/atlanhq/agent-toolkit

Made for: Cursor.

Per session 1,138 This file is loaded in full into every session.
When invoked 1,138 The same file — it is already loaded in full.
Security scan A 0 findings. Scan, not verified.
Origin original No closer match found in the catalogue.
Token cost

What it costs to keep this loaded

Counted locally with the o200k_base tokenizer, which is exact for GPT models; Claude uses its own tokenizer and its counts differ. Treat this as one consistent yardstick across the catalogue rather than a bill. Prices are per million input tokens.

ModelPer sessionOnce invoked
Fable 5 $0.01138 $0.01138
Opus 5 $0.00569 $0.00569
Sonnet 5 $0.00228 $0.00228
Haiku 4.5 $0.00114 $0.00114

Measured 2d ago against content hash 0db7ddd300d5, method: parsed. Prices are Anthropic first-party input rates as of 2026-08-30, from the pricing page.

Security

Grade A, and why

tool-development-guide scanned grade A with 0 findings against 26 rules in 11 categories — prompt injection, anti-refusal, data exfiltration, privilege escalation, supply chain, agent snooping, system-prompt leakage, SSRF and excessive agency — measured 2d ago.

A static scan of the body, not an audit. Every finding is printed with the line that produced it so you can judge whether it matters here. A mod is markdown that instructs an agent; that is exactly why what it instructs is worth reading.

Nothing flagged

None of the 26 patterns this scan looks for appear in this file: no shell pipes, no recursive deletes, no credential paths, no hidden text, no instruction-override or anti-refusal phrasing, no agent-config snooping. That is not a guarantee, it is the absence of the things that are checkable.

modelcontextprotocol/.cursor/rules/tool-development-guide.mdc · 202 lines

How it starts

The opening of the file, as written. The whole thing — 202 lines — stays where its author put it; the contents beside it link to each section on GitHub.

This guide outlines the core coding patterns for implementing tools in the Atlan MCP server.

Tool Implementation Pattern

  1. Define core function in tools.py
  2. Register function as MCP tool in server.py
  3. Use appropriate type hints for PyAtlan and MCP compatibility

Core Function Template (tools.py)

def implement_atlan_tool(
    param1: str,
    param2: Optional[int] = None,
    param3: Optional[Dict[str, Any]] = None
) -> Any:
    """
    Implement an Atlan tool with appropriate parameters.
    """
    logger.info(f"Starting tool execution with parameters: param1={param1}")

    try:
        # Tool-specific implementation
        result = execute_atlan_operation(param1, param2, param3)

        logger.info(f"Tool execution completed successfully")
        return result
    except Exception as e:
        logger.error(f"Error executing tool: {str(e)}")
        logger.exception("Exception details:")
        return get_appropriate_default_value()

MCP Tool Registration Template (server.py)

@mcp.tool()
def registered_tool_name(
    param1: str,
    param2: Optional[int] = None,
    param3: Optional[Dict[str, Any]] = None
) -> Any:
    """
    Tool description with clear purpose.

    Args:
        param1: First parameter description
        param2: Second parameter description
        param3: Third parameter description (complex structure)

    Returns:
        Description of return value

    Example:
        registered_tool_name("value1", 42, {"key": "value"})
    """
    return implement_atlan_tool(param1, param2, param3)

Common Operation Patterns

Asset Search Operation

def search_operation(criteria):
    search = FluentSearch()
    # Add filters based on criteria
    request = search.to_request()
    results = list(atlan_client.asset.search(request).current_page())
    return results

Asset Retrieval Operation

def get_asset_operation(qualified_name, asset_type):
    try:
        asset = asset_type.get_by_qualified_name(
            qualified_name=qualified_name,
            min_ext_info=True,
            atlan_client=atlan_client
        )
        return asset
    except Exception as e:
        logger.error(f"Failed to get asset: {e}")
        return None

Read the full file on GitHub · 202 lines

Changes

What this file has done since we first saw it

Hashed on every crawl. A supply-chain change to an agent config is a question of when, not whether, so the history is kept rather than the latest state alone.

  1. 2d ago First seen · 202 lines · 1,138 tokens per session scan A 0db7ddd300d5

Subscribe to this mod's changes

tool-development-guide is a cursor rule published in the GitHub repository atlanhq/agent-toolkit (32 stars, last pushed 4d ago), licensed MIT. It adds 1,138 tokens to every session, about $0.0057 per session on Opus 5. A static security scan graded it A with 0 findings. No closer match exists in the catalogue, so it is treated as the original; first seen 2026-08-30.