MCP server

Costable — Parametric Should-Cost Analysis

io.github.1337mofo/costable

Checked 25 Oct 2026, 20:29 UTC · Connected to it and listed its tools

Parametric should-cost: P50/P80/P90 estimates, 801 materials, 25 countries, quote review.

At a glance

Type

MCP server

Publisher

Not verified

Status

Working at last check

Tools

10

Token cost

About 2,196 tokens per request

Sets up in

Claude Code, Claude Desktop, Codex, Gemini CLI, Cursor, VS Code, Antigravity, ChatGPT, OpenAI API, Grok

Last checked

25 Oct 2026, 20:29 UTC

Connect it to your agent

Add to CursorAdd to VS CodeVS Code Insiders

Opens the app, which shows the server and asks you to confirm. For other apps, copy the setup below.

Claude Code

claude mcp add --transport http costable https://costable.ai/api/mcp

Claude Desktop

Settings → Connectors → Add custom connector, and paste the URL.

Codex (config.toml)

[mcp_servers.costable]
url = "https://costable.ai/api/mcp"

Gemini CLI

{"mcpServers":{"costable":{"httpUrl":"https://costable.ai/api/mcp"}}}

Cursor

{"mcpServers":{"costable":{"url":"https://costable.ai/api/mcp"}}}

VS Code

{"servers":{"costable":{"type":"http","url":"https://costable.ai/api/mcp"}}}

Antigravity

agy mcp add costable https://costable.ai/api/mcp

ChatGPT

Settings → Apps & Connectors → Advanced settings: turn on Developer mode, then Create a connector and paste the URL. Which plans can do this varies.

OpenAI API (Responses tools)

{"type":"mcp","server_label":"costable","server_url":"https://costable.ai/api/mcp","require_approval":"always"}

Grok (xAI API tools)

{"type":"mcp","server_label":"costable","server_url":"https://costable.ai/api/mcp"}

Tools

• add_material_to_model ~232 tokens
  Add a material (BOM line) to an existing cost model. Searches the materials database by name query — no need for exact IDs.
• add_process_to_model ~323 tokens
  Add a manufacturing process step to an existing cost model. Searches the process database by name query — no need for exact IDs.
• calculate_cost_model ~114 tokens
  Run the Monte Carlo should-cost calculation on a cost model. Returns P50 (median), P80 and P90 cost-at-risk per unit, plus a full cost breakdown (material, labour, machine, overhead, margin).
• compare_manufacturing_countries ~164 tokens
  Run the cost model across multiple manufacturing countries simultaneously to identify the optimal sourcing location. Returns P50/P80/P90 per country and % delta vs baseline.
• create_cost_model ~264 tokens
  Create a new parametric cost model in Costable. Returns the model ID which is used by add_material_to_model, add_process_to_model, calculate_cost_model, and compare_manufacturing_countries.
• estimate_part ~287 tokens
  Instantly estimate the should-cost of a manufactured part using natural language. Returns P50 (median), P80 and P90 cost-at-risk per unit based on Monte Carlo simulation of material price variance, labour rate variance and cycle time uncertainty. Use this for quick feasibility checks before building
• get_labour_rates ~108 tokens
  Get manufacturing labour rates ($/hr) for all skill levels in a given country. Data covers 16 skill levels across 25 countries (ILO/BLS/ABS sourced).
• review_supplier_quote ~319 tokens
  Analyse a supplier quote against Costable's should-cost benchmarks. Returns a line-by-line delta (% over/under should-cost), verdict (LOW / COMPETITIVE / HIGH / VERY HIGH), and a list of the top items to challenge in negotiation.
• search_materials ~197 tokens
  Search the Costable materials database (37 materials with LME-sourced pricing). Returns material name, category, price per kg, density, and strength properties.
• search_processes ~188 tokens
  Search the Costable manufacturing process database (41 processes). Returns process name, category, machine rate ($/hr), and cycle time model.

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