"Information or Context Related to 'Claude'" matching MCP servers:

Provides live wait times and office details for all 60 Oregon DMV field offices by scraping the ODOT website, with no authentication required.

An MCP server that keeps raw tool output out of the context window by sandboxing and compressing results (about 98% reduction), persisting file edits, git operations, tasks and decisions in SQLite with BM25 retrieval so the agent resumes after compaction, and enforcing routing across 17 platforms via MCP and hooks. It also encourages the model to write scripts that compute answers and log only results instead of reading large data into context.

A context window optimizer and session rotator MCP server for agentic workflows that prevents LLMs from running out of context by compacting chat history and rotating sessions.

Enables AI assistants to query PostgreSQL, MySQL, SQL Server, Oracle, and MongoDB databases through MCP with read-only, audited access.

Enables AI agents to browse, trade, and create prediction markets on Context Markets. Supports wallet management, order placement, and market creation through MCP tools.

A local MCP server that acts as a policy-based firewall for personal context, letting users control agent access to their data with deny-by-default rules, per-field grants, and an audit trail.

A Model Context Protocol (MCP) server designed to easily dump your codebase context into Large Language Models (LLMs).

This MCP server lets AI agents connect to Figma to read, analyze, create, and modify designs, including elements, styles, assets, and code generation. It works with free Figma accounts and supports parallel multi-agent use across MCP-compatible clients.

Enables AI agents to compose MCP tool calls into Unix-style pipelines, executing complex workflows server-side and returning only the final result.

Graph RAG based context management engine for coding agents

Enables semantic search of project documentation using hybrid vector and full-text search with fast and deep query modes for immediate results or complex multi-round synthesis.

Enables AI agents to perform corpus analysis tasks such as discovery, search, and data access via the Model Context Protocol.

Indexes your codebase so AI coding agents can search instead of re-reading files, saving up to 94% of tokens.

Enables searching job listings on joblet.ai by title, company, location, and employment type, and retrieving full job details including description, responsibilities, requirements, salary, and apply link.

Enables querying context about the MAM product components and architecture through MCP, allowing agents to retrieve targeted product information on demand instead of loading full documentation.

MCP server providing persistent memory for LLMs via semantic search over captures, structured facts with temporal tracking, and document ingestion. Enables any MCP-compatible client to maintain a searchable knowledge base across sessions.

Provides Stackpress framework context and documentation to AI utilities like Claude Desktop and Cline. Enables AI assistants to understand and work with Stackpress projects by fetching and serving relevant framework information.

Enables agents to transform tabular Markdown content into structured, type-inferred records with normalized formatting through an MCP-compatible interface.

Enables converting Markdown and HTML tables into structured JSON records with automatic column type inference and format normalization. It also offers supporting web-agent primitives such as DOM semantic pruning, form field auto-mapping, and execution trajectory evaluation, all via a zero-dependency MCP server.

Enables agents to break high-level business objectives into dependency-ordered sub-task graphs and then directly generate the finished deliverables, such as financial spreadsheets, executive presentations, and analytical reports. It runs as a zero-dependency Python MCP server over JSON-RPC stdio, adding deterministic authorization, role-boundary validation, and telemetry.