"Construction cost estimate information" matching MCP servers:

Analyze V8/Chrome CPU profiles in Next.js & Node.js apps. Hotspots, package cost attribution, and optimization suggestions for MCP clients like Claude Code and GitHub Copilot

Scan codebases for LLM API calls and estimate monthly costs. Compare costs between git refs to catch cost regressions during code review.

Enables AI assistants to audit Solidity smart contracts for security vulnerabilities, fetch verified source code from block explorers, decode calldata, and estimate gas costs across major EVM networks.

MCP server providing dependency and package management tools for AI agents. Analyze licenses, find outdated packages, visualize dependency trees, estimate bundle sizes, and audit security vulnerabilities.

Exposes boyter/scc code counting and complexity analysis to LLM agents via read-only tools like counting lines, finding top files, and cost estimation.

The server facilitates natural language interactions for exploring and understanding codebases, providing insights into data models and system architecture using a cost-effective, simple setup with support for existing Claude Pro subscriptions.

A zero-cost MCP server that forces AI to self-correct code using prompt injection and context isolation.

Enables whole-codebase code search using natural language queries by leveraging DeepSeek's 1M context window. Automatically shards large projects and utilizes prefix caching for cost-effective repeated searches.

A local, zero-dependency MCP server that cuts coding-agent round-trips by aggregating search, read, edit, exec, git, and savings tools into single, validated calls, with cost tracking and no data leaving the machine.

Enables agents to grade other MCP servers for LLM usability, covering descriptions, schema design, naming, token cost, and consistency, while also explaining grading rules.

Enables AI agents to efficiently read Python code by first providing file skeletons then fetching only needed implementations, reducing noise and cost.

Enables AI coding agents to inspect Runable projects over MCP, providing read-only access to project information and configuration via Runable's inspector.

Provides function-level structural retrieval for coding agents using tree-sitter, with zero-LLM indexing and MCP serving, enabling exact function localization and cost savings.

Intelligent code knowledge graph MCP server for AI coding agents that reduces cost, time, and tool calls by providing queryable code relationships, call chains, and enrichment.

Enables agents to query information about gems in a Ruby project's Gemfile, including source code and metadata.

Provides code generation and completion capabilities using the DeepSeek API, with support for tool chaining and cost optimization.

Local-first MCP server for AI coding agents that provides isolated code search, memory ledger, context rot detection, and cost governance.

A zero-cost, multi-server MCP suite that provides a unified gateway and LangGraph-based automated PR-review agent, enabling code analysis, GitHub operations, and documentation generation via free-tier APIs.

Local-first MCP toolkit that provides coding agents focused repository context via read_file, search_files, and edit_file tools, reducing token usage and task cost.

A read-only MCP server providing structured code planning and review tools (techlead.plan and techlead.review) with multi-provider routing and cost estimation.