"Information about PG Vector" matching MCP servers:

Enables auto-configuration and validation of React components against a glassmorphic design token system using an AST correction engine. It supports managing UI presets, enforcing design uniformity in Monaco IDE, and exporting tokens as CSS, Tailwind, or JavaScript variables.

Extracts deterministic architecture maps from codebases for AI agents, enabling queries about blast radius, routes, security findings, and production readiness without sending code anywhere.

Enables AI assistants to understand and analyze Spring Boot codebases through static analysis, allowing natural language queries about endpoints, classes, dependencies, and architecture without running the application.

Enables AI agents to create, validate, and manage buildingSMART IDS (Information Delivery Specification) files with 100% compliance to the IDS 1.0 standard using IfcOpenShell's IfcTester library.

Semantic React/TSX analysis MCP server that saves 70-90% tokens by using AST to retrieve precise component usages, prop flow, and state update information for AI coding assistants.

Enables coding agents to create and incrementally patch a versioned Figure IR, lay out and lint figures, and render publication-ready vector SVG, PDF, and PPTX files through structured MCP tools.

Enables AI assistants to check server status, inspect Camunda Hub API v2 connection information, and read Hub files by UUID, with planned support for prompt-driven BPMN diagram creation, editing, validation, and visual review.

Enables users to architect, validate, scaffold, and generate production-ready code for Milvus vector database applications. Exposes tools for schema validation, design pattern search, CRUD generation, vector and range search blueprints, and MCP client configuration.

Enables AI agents to query a repository's verified semantic model, including capabilities, ownership, contracts, constraints, impact, health, and verification status, without re-deriving project facts. It exposes read-only tools for inspecting, reasoning about, and verifying the provenance-tracked surface.

Enables AI coding agents to create and iteratively edit native Ipe vector figures for academic papers via natural language, with transactional batches, stable object IDs, LaTeX-measured text, and native undo in the live GUI.

Enables managing Cacoo diagrams, folders, organizations, and account information through MCP tools over HTTP, with OAuth-based authentication, email allowlisting, and support for multiple Cacoo accounts.

Enables AI agents and reviewers to query a deterministic code dependency graph for callers, routes, pages, tables, and config with file:line evidence instead of grepping. One server can serve many indexed graphs, supporting cross-repository impact analysis.

Enables mathematical and scientific computations including linear algebra operations (matrices, eigenvalues, decompositions), vector calculus (gradients, curl, divergence), and visualization of vector fields and functions.

Retrieves architectural information from ArchiMate models, enabling AI coding assistants to access architectural context during the software development lifecycle. Supports search and retrieval of views and elements in markdown, JSON, or YAML.

Builds a dependency and topology graph of a Kubernetes/FluxCD GitOps repository via static analysis, enabling AI agents to reason about service relationships without cluster access.

Enables AI assistants to programmatically create and manage information flow diagrams — information items and information flows in StarUML.

Enables users to start from a seed host, traverse CDP/LLDP neighbor evidence and device information over SSH, and produce an editable Draw.io topology diagram plus supporting evidence for engineer review. It supports explicit host/CIDR scoping, bounded depth and device counts, strict host-key checks, and a read-only command policy, with an offline simulated demo.

Provides a semantic understanding of your codebase by parsing with tree-sitter and building a graph of symbols and dependencies. Enables AI assistants to navigate code, analyze changes, and discover architecture using 18 tools with minimal context overhead.