"Searching for information about DeepSeek" matching MCP servers:

Enables using DeepSeek models as a small, cheap supervised worker from any MCP-compatible client, providing fast flash and deep reasoning tools for bounded tasks.

Local MCP server that provides DeepSeek-powered code review, file analysis, and consultation tools for coding agents, enabling read-only analysis with minimal token overhead.

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.

This MCP server exposes DeepSeek V4 to Codex as a single tool, enabling GPT Sol to delegate coding subtasks to DeepSeek for cheap execution.

Enables a Codex/GPT conversation to request independent second opinions from DeepSeek through a local stdio MCP tool and receive provider-reported model metadata for response or synthesis.

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.

A server that enhances Claude's reasoning capabilities by integrating DeepSeek R1's advanced reasoning engine to tackle complex reasoning tasks.

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.

Generates or reviews Git unified diffs via DeepSeek API with local path validation, enabling secure patch suggestions without scanning repositories.

A Model Context Protocol (MCP) server that provides access to DeepSeek-R1's reasoning capabilities, allowing non-reasoning models to generate better responses with enhanced thinking.

Enables Codex to delegate separable work to DeepSeek Flash/Pro agents through start, continue, status, and cancel tools, while Codex retains tool execution, authorization, and final verification.

Connects MCP clients to DeepSeek API, including DeepSeek-R1 reasoning with visible chain-of-thought. Provides four tools: generate, chat, reason, and list models.

Lets any MCP-capable AI coding harness route code reviews and codebase questions through DeepSeek's web chat, exposing review, ask, and status tools with read-only repository access by default.

Exposes the full DeepSeek API surface — chat, reasoning, fill-in-the-middle, prefix completion, function calling, JSON mode, logprobs, streaming, multi-turn sessions, and local file analysis — to any MCP client, alongside a raw passthrough tool for arbitrary endpoints and parameters. Defaults are deliberately uncapped, with opt-in environment variables for token limits, output truncation, and filesystem confinement.

Provides code generation and completion capabilities using the DeepSeek API, with support for tool chaining and cost optimization.

A local HTTP proxy and MCP server that translates 'developer' role messages to 'system' for DeepSeek API, enabling Android Studio AI plugins to work without errors.

Provides tools to check DeepSeek account balance, list available models, and estimate costs from token usage, without proxying API calls.

MCP server that wraps DeepSeek's AI capabilities into standard MCP tools, supporting three authentication modes including free web-based usage without API keys.

MCP server that lets AI agents discover, inspect, install, and run DeepSeek Harness plugins via MCP, bridging the gap between the MCP protocol and Cordis-based plugin bundles.

Enhances Claude's reasoning capabilities by integrating DeepSeek R1's advanced reasoning engine for intricate multi-step reasoning tasks with precision and efficiency.

Connects a DOT main chat to an already-running Harness instance so it can submit native tasks with progress, replies, queue controls and verified cancellation, page through original history, run keyword history searches, and discover project files with bounded line/tail reads and literal content search. It also handles native interactions, permission reconciliation and explicitly scoped deployment planning and evidence reads, with stable run/operation IDs and idempotency keys for recovery after timeouts or disconnects.

Provides reasoning content to MCP-enabled AI clients by interfacing with Deepseek's API or a local Ollama server, enabling focused reasoning and thought process visualization.

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.

Runs a local HTTP proxy that intercepts chat completion requests and rewrites the developer role into system so Android Studio AI plugins can talk to the DeepSeek API without variant errors. It also exposes an MCP endpoint that Android Studio can discover and connect to, making the role translation transparent during normal AI chat.

Turns a codebase into a persistent knowledge graph so AI coding agents can answer structural questions about functions, call chains, routes, and cross-service links through graph queries instead of reading files one by one.

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

Enables Codex to consult Claude Code for a second opinion through a local stdio MCP server, exposing the ask_claude tool for text-only reviews and recommendations using existing Claude Code authentication. Codex can request findings and tradeoff analysis without allowing Claude to edit files or run commands.

Use Codex as a subagent inside Claude Code: async dispatch into a long-lived codex app-server, results pushed back into the Claude session automatically, steer/interrupt mid-task, and Codex's built-in code review.

Odds are, most of what you want to build is already open source. Tell your AI agent what you're making, and it finds it: which repos to use as they are, which to adapt, and what's left for you to write. Every repo it names is real, licensed for your use or flagged, and checked live.

Provides comprehensive system diagnostics and hardware analysis through 10 specialized tools for troubleshooting and environment monitoring. Offers targeted information gathering for CPU, memory, network, storage, processes, and security analysis across Windows, macOS, and Linux platforms.