"How to Use or Manage Knowledge Base in Feishu" matching MCP servers:

Provides a read-only MCP interface to the Santismm Knowledge Platform, offering tools to retrieve curated content on engineering, AI patterns, architectures, governance, and agent taxonomy with structured output in English, Spanish, and Portuguese.

Enables file-based knowledge management with ranked keyword and semantic hybrid search, allowing AI agents to learn from documents and recall relevant knowledge as a persistent memory tool.

An MCP server that integrates AI agents with Figma, enabling reading and programmatic modification of designs.

Enables AI agents to directly control Figma Desktop via MCP, supporting UI creation, editing, prototyping, and variable management with over 60 tools.

Enables AI models to access and search offline Wikipedia and other knowledge bases stored in ZIM format files. Provides intelligent content retrieval, structured browsing, advanced search capabilities, and metadata extraction for comprehensive offline knowledge access.

An MCP server that turns AI assistants into competent Festo/CODESYS PLC engineers by grounding them in curated, manufacturer-accurate knowledge and forcing every artifact through a machine-checked validation pipeline for CODESYS import.

Provides enterprise architecture knowledge tools that ground agents in curated patterns, enabling translation of messy enterprise asks into realistic architecture recommendations, platform selection, risk checks, and brand context retrieval.

Track how your brand appears in AI-generated answers across ChatGPT, Perplexity, and other AI models. Analyze visibility, sentiment, citations, and domain rankings with 31 tools — including analytics reports, chat inspection, query analysis, and full CRUD for brands, prompts, tags, and topics.

Provides a Model Context Protocol server with tools for knowledge base search, retrieval, and addition, plus system time, resources, and prompts. Supports stdio and Streamable HTTP transports for local and shared deployments.

A simple MCP server that provides a basic greeting tool and serves as a starter template for AWS Lambda deployment. Demonstrates how to build and deploy MCP servers with both local development and cloud deployment capabilities.

AI job search and job application tracker. Search live jobs by title, location, salary, date posted, and remote or on-site, and see each one checked on real data: pay against market rates, ghost-job signals, visa sponsorship history, and how well it matches your resume. Check how hiring software reads your resume, track applications, set follow-up reminders, and get email alerts.

Enables AI assistants to perform institutional research and due diligence by retrieving, extracting, validating, and citing data from public sources, then generating reports in markdown, HTML, or PDF.

Enables persistent, auditable business operations state by storing knowledge, evidence, decisions, tasks, execution receipts, and review results in a local SQLite database, so different sessions can continue the same project.

tdmcp is an open-source (MIT) Model Context Protocol server for TouchDesigner. You describe a visual in plain language and your AI assistant builds the real node network inside TouchDesigner, checks it for errors, and shows a preview — it ships an embedded operator knowledge base so the model uses real operators instead of guessing. TypeScript codebase, runs locally.

Enables AI assistants to read and modify Figma designs programmatically through the Model Context Protocol.

A SitecoreMCP version that can be used in enterprises

Exposes GOV.UK Frontend components and Design System patterns and styles as MCP resources for use with AI assistants.

A lightweight MCP server that enables AI assistants to execute local development tools and retrieve system status with low latency over stdio or HTTP.

An MCP server that provides AI clients with access to developer documentation via llms.txt files. Exposes tools, resources, and prompts.

A local-first, no-API-key MCP server that enables LLMs to search the web, fetch pages, and read documents using multiple engines and smart fallbacks.