"Tips and tools for creating a graph" matching MCP servers:

Enables querying a TypeScript codebase's graph for call flows, type relationships, and symbol locations without reading file bodies.

MCP server that exposes the OBBBA No Tax on Tips federal deduction logic as callable tools, enabling users to check eligibility and estimate tip deductions.

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.

An MCP server that gives your agent a persistent project brain: vision, architecture decisions, conventions, roadmaps, and automatic session handoff.

Enables AI agents to perform local video, audio, and file operations inside an isolated workspace, including cutting/concat videos, extracting audio, transcribing, and managing files, with typed responses and background job support.

Enables agents to compress JPEG, PNG, and WebP images to a target byte size, split PDFs by page or ranges, and remove image metadata while processing local files without sending file bytes over the network.

Enables to perform mathematical calculations, retrieve weather information, and manage files through a standardized MCP interface, showcasing best practices for building MCP servers.

Exposes a Neo4j knowledge-graph index over personal markdown notes to LLM agents via MCP, enabling semantic search, tag navigation, and relationship discovery.

Graph-MIND records every conversation you have with Claude Code, Codex and Claude Desktop, word for word, in a store on your own PC. When a question depends on the past, the model you are using calls Graph-MIND over MCP and gets back a few thousand tokens of the conversations that answer it.

Exposes a dependency graph of strategic sourcing artifacts and analyses as an MCP server, enabling navigation of phases, analyses, deliverables, and graph traversal for impact analysis and build order.

MCP server enabling Claude Code to capture screenshots of Windows applications through WSL2, allowing AI to diagnose UI errors and verify layouts.

Enables coding agents to query a deterministic AST knowledge graph of a codebase over MCP—finding symbols, callers/callees, dependencies, impact, and relevant tests via compact path:line JSON—so they can navigate code without grepping, embeddings, or an LLM.

Provides AI coding agents with a local knowledge-graph memory, enabling cross-project retrieval via PageRank diffusion and tools to retrieve, write, extract, update, and view recent knowledge over MCP.

Enables LLMs to perform OSINT link-analysis by exposing transforms (DNS, WHOIS, Shodan, etc.) as MCP tools for autonomous investigation and graph enrichment.

Provides a decision memory layer for codebases, enabling AI agents to search, retrieve, and record business decisions with metadata filters and full-text search.

Maps Salesforce metadata into a Neo4j graph database, enabling AI agents to reason about schema and generate accurate SOQL queries.

A-MEM is a self-evolving memory system for coding agents that automatically organizes knowledge into a Zettelkasten-style graph with dynamic relationships, enabling semantic and structural search.

Enables AI agents to control a Playwright-driven browser through natural-language instructions, including page interaction and live browser task execution.

Enables Claude Code and other MCP clients to query a local, explainable knowledge graph of a codebase: answering questions, explaining symbols, tracing paths between them, and computing blast-radius impact, with every edge backed by file:line evidence. Read-only and fully offline — no network calls, telemetry, or runtime dependencies.

A knowledge graph MCP server that indexes your codebase into a local SQLite graph and provides tools for project mapping, file summaries, and impact analysis, drastically reducing token usage in AI coding assistants.