Skip to main content
Glama
zesun33

@zesun33/mcp-openroad

by zesun33

openroad_place

Places standard cells on a floorplan DEF using RePLace global analytical placement and DPL legalized detailed placement, producing a placed DEF for physical design flow.

Instructions

Performs standard cell global analytical placement (RePLace) and legalized detailed placement (DPL) on a floorplan DEF file.

Input Schema

TableJSON Schema
NameRequiredDescriptionDefault
cwdNoOptional working directory.
densityNoTarget placement density (default: 0.4).
output_defNoOutput placed DEF file path.
timeout_msNoTimeout in milliseconds.
top_moduleYesName of the top-level module.
floorplan_defYesFloorplan DEF file path.

Schema Changelog

Changes observed during successful MCP inspections. Dates show when Glama detected each change.

  1. First observedv0.1.0

TDQS

B3.4/5.0
Behavior2/5

Does the description disclose side effects, auth requirements, rate limits, or destructive behavior?

There are no annotations, so the description carries the full burden of disclosing side effects, safety, and preconditions. It only restates the placement operation and says nothing about whether the input DEF is modified, whether an output file is written, or what failure conditions exist. This is a significant transparency gap for a transformation tool.

Agents need to know what a tool does to the world before calling it. Descriptions should go beyond structured annotations to explain consequences.

Conciseness5/5

Is the description appropriately sized, front-loaded, and free of redundancy?

A single front-loaded sentence that states the verb, scope, and target file type in one pass. There is no repetition of schema fields and no filler, making it highly concise and efficient.

Shorter descriptions cost fewer tokens and are easier for agents to parse. Every sentence should earn its place.

Completeness2/5

Given the tool's complexity, does the description cover enough for an agent to succeed on first attempt?

With six parameters, no annotations, and no output schema, the description should explain prerequisites, side effects, and expected results. It only covers the transformation itself, leaving the agent to guess about flow order and what the tool returns or writes.

Complex tools with many parameters or behaviors need more documentation. Simple tools need less. This dimension scales expectations accordingly.

Parameters3/5

Does the description clarify parameter syntax, constraints, interactions, or defaults beyond what the schema provides?

Schema description coverage is 100%, so the baseline is 3. The description adds general context about the placement operation but does not elaborate on parameters like density or output_def beyond their schema descriptions.

Input schemas describe structure but not intent. Descriptions should explain non-obvious parameter relationships and valid value ranges.

Purpose5/5

Does the description clearly state what the tool does and how it differs from similar tools?

The description opens with a specific verb ('Performs'), names the resource ('standard cell ... placement'), and distinguishes the step by naming both global analytical placement (RePLace) and legalized detailed placement (DPL). This clearly differentiates it from sibling floorplan, route, and STA tools.

Agents choose between tools based on descriptions. A clear purpose with a specific verb and resource helps agents select the right tool.

Usage Guidelines3/5

Does the description explain when to use this tool, when not to, or what alternatives exist?

The placement step is implied by the operation and the sibling tool names, but the description never explicitly states when to use this tool versus openroad_floorplan, openroad_route, or openroad_pnr, nor does it mention prerequisites. An agent can infer usage context only from the tool name and flow terminology.

Agents often have multiple tools that could apply. Explicit usage guidance like "use X instead of Y when Z" prevents misuse.

Latest Blog Posts

MCP directory API

We provide all the information about MCP servers via our MCP API.

curl -X GET 'https://glama.ai/api/mcp/v1/servers/zesun33/mcp-openroad'

If you have feedback or need assistance with the MCP directory API, please join our Discord server