"Examples of DeepSeek-related applications or projects" matching MCP servers:

Copy-paste MCP configs for Palim hosted cross-tool memory (Claude, Cursor, ChatGPT).

Enables semantic search over local knowledge bases like Obsidian notes, SQLite, and plaintext files, exposing results to Claude via MCP server.

Enhances Claude's reasoning capabilities by integrating DeepSeek R1's advanced reasoning engine, allowing Claude to tackle complex multi-step reasoning tasks with greater precision.

AoT MCP server enables AI models to solve complex reasoning problems by decomposing them into independent, reusable atomic units of thought, featuring a powerful decomposition-contraction mechanism that allows for deep exploration of problem spaces while maintaining high confidence in conclusions.

Enables sophisticated reasoning workflows using graph-based representations for AI models.

A scientific reasoning framework that leverages graph structures and the Model Context Protocol (MCP) to process complex scientific queries through an Advanced Scientific Reasoning Graph-of-Thoughts (ASR-GoT) approach.

An MCP server for managing contextual data as markdown files with metadata, enabling agents to save, retrieve, search, and delete contexts using simple CRUD operations.

Project Memory stores decisions, evidence, outcomes and reviewed lessons in local SQLite. Assistants retrieve bounded context through three MCP tools. People follow and plan work in a live workspace with an overview, sprint board, decision history, readable documents, skills and project maps. Offline exports remain available.

Provenance tree for work: every node knows which node it was born from

A read-only MCP server that lets AI agents search and retrieve the Wheel of Heaven corpus, including source-grounded facts, interpretations, and comparative traditions, all with full epistemic metadata.

Shelfmark is an MCP server that builds a local metadata catalogue of your documents, enabling AI agents to discover, search, and select relevant files without opening or indexing their contents. It provides governed access with ownership and confidentiality controls, ensuring agents only see what they are permitted to.

Enables context capture and reinforcement learning by recording successful work patterns and creating reasoning chains for cross-conversation continuity. Automatically captures positive feedback through Claude Code hooks to build reusable success patterns.

Transforms Claude into a persistent intelligence layer with automatic checkpointing, crash recovery, semantic memory, and cross-project learning. It provides 128+ tools for session management, adversarial testing, and browser automation to eliminate state loss and context rebuild costs.

Provides persistent local memory of Claude Code sessions with TODO management and searchable activity logs via MCP tools.

Provides session persistence, crash recovery, decision tracking, and context compression for AI assistants, enabling seamless multi-session continuity.

Enables Claude Code to search, browse, and read its own past conversation history across all projects using BM25 keyword search.

Provides tools for managing qualitative research knowledge graphs, enabling structured representation of research projects, participants, interviews, observations, codes, themes, and findings.

Provides tools for managing quantitative research knowledge graphs, enabling structured representation of research projects, datasets, variables, hypotheses, statistical tests, models, and results.

Provides tools for managing project knowledge graphs, enabling structured representation of projects, tasks, milestones, resources, and team members.

Enables users to access, search, and get recommendations from AWS documentation through natural language queries. Supports both global AWS documentation and AWS China documentation with tools to fetch pages, search content, and discover related resources.