"How to make a model aware of the current time before thinking" matching MCP servers:

Model-agnostic code memory MCP server using budget-aware graph retrieval for AI agents, providing sub-millisecond queries, token budgeting, and deterministic results without embeddings or vector databases.

Enables querying Odoo's model registry (fields, inheritance, methods) without a database connection by loading the registry in-memory.

An MCP server for static Big-O time complexity analysis using tree-sitter AST parsing. Supports JavaScript, TypeScript, Python, Java, Kotlin, and Dart.

Provides MCP tools for searching a codebase with exact file:line citations, reading specific source spans, and inspecting index stats, enabling agents to retrieve and cite code accurately.

Enables checking project files like Dockerfile, .nvmrc, and CI workflows to determine whether pinned runtime, database, and OS versions are still supported, providing end-of-life dates, latest patches, and upgrade targets for 470+ products.

Enables AI assistants and developers to analyze code for language-specific best practices and idiomatic patterns across programming languages, CI automation, and configuration formats.

A validation layer for AI coding assistants that enforces explicit LLM evaluations on plans, code diffs, and tests to ensure safer and higher-quality code.

A local MCP server that lets Claude Code and Codex delegate repository exploration and test proposals to a remote LM Studio model, while enforcing security boundaries by keeping all repository access read-only and never applying patches or running commands remotely.

Exposes 11 agent-native QA tools over stdio so coding agents can discover a project, analyze risk, select the smallest relevant test set, generate and dry-run tests, triage failures, propose tiered heals, analyze flakes, generate quality reports, and evaluate release readiness. Planning and healing tools stay read-only or propose-only, while execution defaults to dry-run, keeping agent actions safe and evidence-backed.

A runtime-free MCP server that converts source code into AST🌲, regardless of language.

Enables AI assistants like Claude to navigate git repository history, providing insights into code evolution and helping understand legacy systems.

Turns GitHub repository history into a cited maintainer skill for coding agents, providing tools to collect evidence, query the knowledge graph, and inspect bundles.

Enables automated migration of Vue projects to React with intelligent analysis, task management, and learning from user modifications.

Enables auditing the AI models and SDKs in a repository, drafting evaluation examples, ranking candidates by cost per passing answer, and generating cheapest-first routing configurations, all through read-only local tools that never make network calls. Also estimates monthly token spend and local weights/KV-cache memory so users can pick and size the cheapest model that passes their own tests.

Enables Claude to use Google Gemini as a secondary AI through MCP for large-scale codebase analysis and complex reasoning tasks. Supports both Gemini Flash and Pro models with specialized functions for general queries and comprehensive code analysis.

Enterprise-grade code intelligence server for AI assistants that analyzes codebases for due diligence, tech debt, security vulnerabilities, and code quality.

A Python-based server for managing and analyzing code context for AI-assisted development. Provides real-time code analysis, project structure analysis, dependency tracking, and secure API endpoints.

Lets AI coding agents read an outline of a large file or a digest of noisy command output instead of the full text, while every hidden line stays retrievable on disk through a run handle. Agents can request only the line ranges, slices, or grep matches they need and list recent runs, cutting token spend without losing information.

Codebase Q&A agent with git-history awareness. Explore a repo with list_files, read_file, and search, plus git log, blame, and diff and a repo map to answer "why did this change?" questions. Runs locally as an MCP server for Claude Code and other MCP clients.

A lean, local knowledge graph that joins a repo's code to its aSPARK delivery artifacts, enabling agents to trace user stories to code and assess impact of changes, served over MCP.

Enables AI assistants to analyze project folders for dependencies and frameworks and fetch current documentation or datasheets from the web.

An MCP server that orchestrates a dual-model workflow using Claude Opus for high-level code generation and Codex for automated code review and bug fixing. It provides tools for framework design, task classification, and quality assurance to optimize software development.

Enables AI agents to run deterministic database intelligence tasks including natural-language-to-SQL synthesis, AST SQL auditing and optimization, schema migration diffing, SQL transpilation, index and normalization advice, PII scrubbing, fixture generation, connection-pool sizing, isolation-hazard auditing, and ORM model compilation over Streamable HTTP or stdio.

Enables developers and AI agents to compress context, plan token budgets, rerank results, patch code, analyze ASTs and dependencies, isolate stack traces, compile polyglot types, solve deterministic math, schedule constraints, judge A/B tests, and diff agent memory checkpoints through 12 specialized tools.

Enables agents to audit and safeguard repositories by detecting dependency pinning issues, license compliance problems, hardcoded secrets, and dead code through MCP tools.

An MCP server that lets AI models run code in 31 languages, evaluate symbolic math and logic problems, and measure complexity—exposed as 48 tools for execution, session management, translation, optimization, and more.

Enables migration of test automation projects from WebDriverIO to Playwright using AST-based transformations. Provides tools for analyzing tests, converting syntax, refactoring to Page Object Model, and generating migration reports.

Converts vector PDF circuit schematics into evidence-preserving SchematicIR JSON with tools to inspect, convert, and validate schematic PDFs.

Enables coding agents to audit a Next.js codebase read-only, checking routes, Prisma models, environment variables, and locale consistency via MCP tools.

Enables MCP clients such as Claude Desktop or Cursor to inspect a coffee-shop sales database schema, validate SQL, and run guarded read-only queries. It supports natural-language questions by exposing tools for schema description, SQL checking, and safe query execution.