"Exploring Memory Persistence in DeepSeek Technology" matching MCP servers:

MCP server that enables Claude Code to delegate tasks to DeepSeek and other LLMs, offering 20 tools for code review, analysis, testing, and code generation.

Persistent memory and pattern learning for AI coding assistants via MCP.

MCP server that packages DeepSeek agents as callable tools, offering a bare model for quick Q&A and a full agent capable of executing real coding and file-modifying tasks in a workspace.

Run DeepSeek as a real sub-agent inside Claude Code / Codex CLI — not just a single LLM call. DeepSeek gets its own 7-tool agent loop (Read/Write/Edit/Bash/Glob/Grep/NotebookEdit) inside a sandboxed workspace.

Enables AI coding agents like Claude Code or Codex to delegate tasks to a DeepSeek Harness subagent with its own context window, providing tools for task delegation, result waiting, continuation, and supervision with sandboxed execution.

Enables delegating bounded development tasks to a locally installed DSH harness and returns a structured handoff covering file writes, command exit codes, missing checks, blockers, and evidence.

Call OpenAI Codex from Claude Code for independent second opinions, structured code review, and delegated coding tasks through a FastMCP plugin that drives the codex CLI safely.

MCP server for DeepSeek AI models (Chat + Reasoner). Supports multi-turn sessions, model fallback with circuit breaker, function calling, thinking mode, JSON output, multimodal input, and cost tracking.

Enables Claude Code to delegate tasks such as planning, coding, reviews, debugging, tests, and docs to a cheaper model that works autonomously in a project-sandboxed loop with file, search, and test tools, returning a compact report to save tokens. Routing rules, approval-gated deletes and commands, per-task model/effort settings, and backups keep the user in control of what gets handed off.

A Codex MCP server that delegates exploration and implementation tasks to DeepSeek via Claude Agent SDK, supporting subagent types and task persistence.

Enables ChatGPT (or any MCP client) to delegate coding tasks to a local Hermes-backed agent with async job management, supporting read-only investigation, implementation, and continuation of sessions via secure MCP tunnel.

Enables a local MCP client to drive an already-open DeepSeek Harness Desktop session over a loopback-only, Bearer-authenticated endpoint — submitting standard-mode tasks, reading bounded output, continuing or canceling runs, and inspecting diagnostics.

Enables Codex to delegate code reviews, coding tasks, image/video generation, and background investigations to Grok via MCP tools.

Enables Codex to start the local DeepSeek Harness Web UI, delegate coding tasks into visible sessions, and review workspace changes.

Enables Codex to launch and orchestrate local agent sessions, delegate tasks, return clickable live web links, and independently verify actual workspace changes.

Enables querying DeepSeek-Flash with configurable chain-of-thought effort and running autonomous code tasks that plan a spec, edit files, run tests, and self-review the resulting diff. Also provides adversarial code auditing, API health and latency checks, plus workspace, command-blacklist, and Git branch safety guardrails.

Enables local AI agents to access DeepSeek V4 models and perform coding tasks via Pi's agent SDK.

Enables Claude Code to delegate bounded repository tasks to DeepSeek as a local sub-agent, handling exploration, routine changes, and test runs within a controlled workspace and budget.

Gives AI coding assistants persistent memory, safety controls, and project awareness by tracking coding sessions, protecting critical files from modifications, and managing approval workflows with automatic changelog generation.

Provides a file-based, git-friendly memory store for coding agents to persist and recall project-specific lessons, bugs, and conventions via JSON files in the repository.

Offloads expensive code reading, editing, and checking tasks to DeepSeek through Claude Code, saving Codex main-thread tokens by 40-60%.

Provides persistent memory for AI coding agents through the Model Context Protocol, enabling them to store and retrieve project knowledge across sessions.

Provides persistent long-term memory for AI coding agents by storing entities, relations, and observations across different sessions. It enables users to manage and query structured knowledge like coding preferences, project patterns, and technical solutions via a graph-based storage system.

An in-memory knowledge graph MCP server that gives coding agents structural and semantic recall over codebases by indexing Python source, ADR documents, and project configuration, exposing 7 tools for search, traversal, context retrieval, and natural-language Q&A.

On-device memory system for AI coding agents that captures commands, edits, and test results in a lossless ledger plus distilled facts, then provides selective recall over MCP with tools like remember, recall, search, and ask.

Provides coding agents with persistent, evidence-backed project memory and knowledge across sessions, using a structured memory tree and local knowledge base.

Provides repository-scoped safe memory for AI coding agents with just-in-time verification against file changes to ensure facts remain accurate. It links memories to specific code citations and automatically marks them as stale if the underlying source code is modified or deleted.

Persistent, local memory for AI coding agents that learns how you work, not just what you said. Supports Claude Code, Codex CLI, Cursor, and any MCP client.

Persistent memory for AI coding agents

Enables three-layer Codex-to-DeepSeek coordination with project memory, task dispatch, worker collection, and workspace permission mapping through an MCP bridge over Codex app-server and Harness.