How to get DeepSeek to work with Cursor’s Agent Mode

DeepSeek exposes an OpenAI-compatible API you can point Cursor at (or route via a gateway like CometAPI). With careful model naming, embeddings checks, and a security review, you can run Cursor’s Agent Mode against DeepSeek models for code generation, refactors, and test-driven workflows.

What is DeepSeek?

DeepSeek is a commercial AI model platform and family of models that offers reasoning-first LLMs and related APIs for text, embeddings, and agent workflows. DeepSeek publishes both web and API access to its models and teams (versions like “DeepSeek-V3.2” and platform endpoints) aimed at building search/assistant/agent experiences. The API is presented as OpenAI-compatible — so tools and clients that let you supply a custom base_url + API key will often work with minimal changes.

DeepSeek-R1: The Reasoning Engine

The introduction of DeepSeek-R1 has been a game-changer for "Agentic" workflows. Unlike standard chat models that rush to an answer, R1 utilizes a "Chain of Thought" (CoT) process similar to OpenAI’s o1 series. In Cursor Agent Mode, this is critical. When an agent is asked to "refactor the authentication middleware and update all dependent tests," it needs to plan before it acts. R1’s ability to verify its own logic reduces the rate of hallucinated file paths and incorrect API calls, making the Agent mode significantly more autonomous.

Breakthroughs in Deepseek V3.2

Released on December 1, 2025, DeepSeek V3.2 introduced two groundbreaking technologies:

DeepSeek Sparse Attention (DSA): Unlike traditional transformers that waste computation by attending to every token, DSA dynamically selects only the most relevant information. This reduces inference costs by approximately 40% while maintaining long-context fidelity (up to 128k tokens). This is crucial for coding agents that need to "read" entire repositories.
Native "Thinking" Mode: While previous models required prompting to "show your work," V3.2 integrates a Chain-of-Thought (CoT) process directly into its architecture. It verifies its own logic before outputting code, significantly reducing the "hallucination rate" in library imports and API calls.

The Looming Arrival of DeepSeek-V4

Industry insiders are currently buzzing about the imminent launch of DeepSeek-V4, rumored for mid-February 2026. Leaks suggest this model will feature a context window exceeding 1 million tokens and specialized "long-context coding" capabilities designed to ingest entire repositories in a single pass. Early adopters setting up their DeepSeek-Cursor pipelines now are effectively preparing their infrastructure for this next leap in capability.

What is Cursor Agent Mode?

If DeepSeek V3.2 is the brain, Cursor Agent Mode is the body. In 2026, the definition of an "IDE" has changed. Cursor is no longer just a text editor; it is an agentic environment.

Beyond Autocomplete

Standard AI coding tools (like the old Copilot) were reactive—they completed the line you were typing. Agent Mode is proactive. It operates as an autonomous loop:

Plan: The agent analyzes the user's request (e.g., "Refactor the authentication module to use OAuth2").
Context Retrieval: It autonomously scans the file system, reading only the relevant files (auth.ts, user_model.go, config.yaml).
Action: It applies edits across multiple files simultaneously.
Verification: Uniquely, Agent Mode can run terminal commands. It will execute npm test or cargo build, parse the error logs, and self-correct its code until the tests pass.

This "Looping" capability is where cost becomes a factor. A single task might require 50 API calls. Doing this with expensive models is prohibitive. Doing it with DeepSeek is negligible.

Why integrate DeepSeek with Cursor Agent Mode?

Benefits

Autonomous coding at your own model choice: If DeepSeek’s models fit your cost/latency/quality profile, you can run Cursor’s agents against them for multi-file refactors, test generation, or CI-style fixes.
Function calling + tools: DeepSeek supports function calling — useful for agents that must orchestrate tooling (run tests, call linters, or create files programmatically).
Flexibility via gateways: You can front DeepSeek with a gateway (like CometAPI) to add routing, policy control, and model multiplexing. This is useful for teams that want a single endpoint to switch providers without changing Cursor settings.

Risks & caveats

Privacy & compliance: DeepSeek has been flagged by national agencies and researchers for data/telemetry questions. Before forwarding proprietary code to DeepSeek (or any third party), run a legal/infosec review and consider on-prem or private gateway options.
Embeddings & searching caveats in Cursor: Cursor features (code search, crawling, embeddings) may break or behave unexpectedly with non-standard embedding endpoints or when model embedding dimensions mismatch. The community has reported embedding problems when base_url was overridden. Test thoroughly.
Model naming and tools support: Cursor expects certain model names or capabilities (e.g., tool support). You may need to present the DeepSeek model with the exact name Cursor expects or configure a custom mode.

Step-by-Step Guide: How to get DeepSeek to work with Cursor Agent Mode?

Below is a pragmatic path with two deployment options: (A) Direct — configure Cursor to talk directly to DeepSeek’s OpenAI-compatible endpoint; (B) Gateway — put CometAPI (or your own lightweight proxy) in front of DeepSeek to centralize routing, policy, and observability.

Pre-reqs: a Cursor installation (desktop or cloud), a DeepSeek API key (from your DeepSeek account), and (for the gateway option) a CometAPI account or your gateway. Test in a disposable repo first — never send secrets or production-only code until you’ve completed security review.

Option A — Direct integration (fastest to try)

1) Verify DeepSeek API access with curl

Replace DSEEK_KEY and MODEL_NAME with your values. This step confirms DeepSeek responds like an OpenAI-compatible endpoint.

# Chat completion style test (DeepSeek OpenAI-compatible)
export DSEEK_KEY="sk-...your_key..."
curl -s -X POST "https://api.deepseek.com/v1/chat/completions" \
  -H "Authorization: Bearer $DSEEK_KEY" \
  -H "Content-Type: application/json" \
  -d '{
    "model":"deepseek-code-1.0",
    "messages":[{"role":"system","content":"You are a helpful code assistant."},
                {"role":"user","content":"Write a one-file Node.js Express hello world"}]
  }' | jq

If you get a valid JSON choices response, proceed. The DeepSeek docs document the base URLs and sample calls.

2) Add DeepSeek as a custom model in Cursor

In Cursor: Settings → Models → Add OpenAI API Key (or equivalent). Use these fields:

API key: paste your DeepSeek API key.
Override OpenAI base URL: enable and set to https://api.deepseek.com/v1 (or https://api.deepseek.com depending on what the docs recommend).
Add model name: add the exact model name DeepSeek exposes (e.g., deepseek-code-1.0 or the model listed in their dashboard).

Notes:

Cursor may require both a valid OpenAI key and the provider key in some versions for activation — follow the verify flow. Users have reported UI quirks in the verification step; if verify fails but curl worked, check Cursor logs or the forum.

3) Create a Cursor Custom Mode tuned for DeepSeek (recommended)

Use Cursor’s Custom Mode to keep a targeted instruction set and tool configuration for DeepSeek-backed agents. Here’s a sample system prompt and rule set you can paste into the Custom Mode UI:

System prompt (example):
You are an autonomous code agent. Use concise diffs when editing files and produce unit tests when you modify functionality. Always run the project's test suite after changes; do not commit failing tests. Ask before changing database migrations. Limit external network requests. Use the provided tooling (file edits, run tests, lint) and explain major design decisions in a short follow-up message.

Rules:
- Tests first: always add or update tests for code changes.
- No secrets: do not output or exfiltrate API keys or secrets.
- Small commits: prefer multiple small commits over a single huge change.

This helps constrain the agent and compensates for any behavioral differences of the model. Cursor’s docs emphasize planning, instructions, and verifiable goals when running agents.

4) Test Agent Mode on a simple task

Ask Cursor in Agent Mode: “Add a unit test that verifies the login endpoint returns 401 for unauthenticated requests, then implement the minimal code so the test passes.” Watch the agent produce a plan, make edits, run tests, and iterate. If it stalls or waits for permission, adjust the system rules or increase the agent autonomy in the Custom Mode options.

5) Troubleshoot embeddings and code search

If Cursor’s codebase search, crawling, or @docs features break when you switch the base URL, it’s likely due to embeddings endpoint differences (dimension mismatch or minor API behavior changes). Troubleshooting checklist:

Generate an embedding with DeepSeek’s embeddings endpoint via curl and verify the vector length.
If the dimensions differ from what Cursor expects, consider using a gateway to normalize embeddings or keep Cursor’s embedding provider as OpenAI (if policy allows), while using DeepSeek for completions only. Embedding-related failures when overriding base_url.

Option B — Integration via CometAPI (recommended for teams)

CometAPI acts as a model gateway that can present a single stable endpoint (and consistent model names) while routing to underlying providers like DeepSeek. That gives you observability, centralized billing, policy hooks, and easier provider switching.

1) Why use a gateway?

Centralized credentials and audit logs.
Model version pinning and traffic routing (A/B test multiple models).
Policy enforcement (strip PII, redact secrets) and caching.
Easier Cursor configuration — you point Cursor at CometAPI once; switching vendors later is a server-side config change.

2) Example CometAPI -> DeepSeek routing (conceptual)

On CometAPI’s console you create a model alias (e.g., deepseek/production) that proxies to DeepSeek’s model endpoint. The gateway may provide an API key and a base_url such as https://api.cometapi.com/v1.

3) Configure Cursor to use CometAPI

In Cursor: Settings → Models → Add OpenAI API Key — use the CometAPI key.
Override base URL: https://api.cometapi.com/v1.
Add the gateway model name (e.g., deepseek/production or the alias you created).

4) Sample curl via CometAPI that routes to DeepSeek

# Request to CometAPI, which routes to DeepSeek under the hood
export COMET_KEY="sk-comet-..."
curl -s -X POST "https://api.cometapi.com/v1/chat/completions" \
  -H "Authorization: Bearer $COMET_KEY" \
  -H "Content-Type: application/json" \
  -d '{
    "model":"deepseek/production",
    "messages":[{"role":"system","content":"You are a careful code assistant."},
                {"role":"user","content":"Refactor function X to improve readability and add tests."}]
  }' | jq

This single base_url makes Cursor configuration simpler, and CometAPI can provide extra options like request throttling, observability, and cost accounting.

What role can CometAPI play in this?

Short answer

CometAPI can act as a model-aggregation gateway between Cursor and DeepSeek. It centralizes authentication, routing, cost controls, failover, and gives you a single OpenAI-style REST interface even if your models come from different vendors.

Practical roles CometAPI can provide

Unified endpoint: Cursor or your server only needs to know one gateway endpoint. You can route to deepseek-v3.2 or fall back to a different provider if DeepSeek is unavailable.
Billing and quotas: CometAPI aggregates usage for billing and policies across models — helpful for cross-team cost allocation.
Model A/B testing: Switch model targets without changing Cursor configuration by updating routing rules in the gateway.
Latency & redundancy: You can configure fallback providers to mitigate outages or regulatory blocks in certain regions.
Simplified auth: Store vendor keys in Comet; Cursor only uses your gateway key (short-lived tokens from your proxy). This reduces exposure.

Example: calling CometAPI to route to DeepSeek (Python)

import requests
COMET_KEY = "sk-xxxxxxxx"
url = "https://api.cometapi.com/v1/chat/completions"

payload = {
  "model": "deepseek-v3.2",   # instruct gateway which model to run
  "messages": [{"role":"user","content":"Refactor this function to be more testable:"}],
  "max_tokens": 1024,
  "stream": False
}

resp = requests.post(url, json=payload, headers={"Authorization": f"Bearer {COMET_KEY}"})
print(resp.json())

Check CometAPI’s docs for exact parameter names and model identifiers — it supports many models and provides usage analytics.

How do tool calls work and what to watch for DeepSeek through Cursor

DeepSeek supports function calling and structured JSON output; Cursor exposes tools (file edit, run terminal, HTTP). When a model emits a function call, Cursor’s agent harness orchestrates tool execution. Two important implementation items:

Function call schemas must match the agent harness — DeepSeek’s function-call payload should be mapped to Cursor’s tool names and argument shapes. Test with a small loop where DeepSeek produces a JSON function call and your gateway (or Cursor) forwards the parsed function to the matching tool.
Thinking mode vs final answer — DeepSeek’s “thinking” (chain-of-thought) mode returns reasoning content and a final answer. Cursor’s agent harness may choose to surface or hide “reasoning” content to the user; for tool calls you usually want the model to finalize arguments before the tool is executed. Read DeepSeek docs on reasoning_content handling.

Example: request that triggers a function call

{
  "model":"deepseek-reasoner",
  "messages":[{"role":"system","content":"You are an autonomous coding agent. Use tools only when necessary."},
              {"role":"user","content":"Run tests and fix failing assertions in tests/test_utils.py"}],
  "functions":[
    {"name":"run_shell","description":"execute shell command","parameters":{"type":"object","properties":{"cmd":{"type":"string"}},"required":["cmd"]}}
  ],
  "function_call":"auto"
}

When DeepSeek returns {"name":"run_shell","arguments":"{\"cmd\":\"pytest tests/test_utils.py\"}"}, Cursor (or your gateway) must route that to the runtime shell tool and capture stdout/stderr and pass results back to the model as observations.

Troubleshooting & FAQs

Q: Cursor shows "403 please check the api-key" when using my DeepSeek key — why?

A: Cursor may route some model requests through its own backend when using Cursor-provided models or it may disallow agent-level BYOK on lower plans. Two remedies: (1) use Cursor’s Add Model UI and verify exact base URL and key semantics; (2) host a proxy that Cursor can call (see Option B) and verify with a direct request to the proxy. Community threads document both behaviors.

Q: Function calls aren’t executed or arguments are malformed.

A: Confirm DeepSeek's function schema and ensure your gateway or Cursor tool mapping matches expected JSON types. Also check whether DeepSeek returned reasoning_content only (thinking trace) and not final function arguments — pass the final resolved content back into a new model turn if necessary.

Q: Agent runs are expensive. How to cap cost?

A: Add hard token/use quotas in the gateway, require human review after N iterations, or schedule runs during off-peak windows. Log token usage to Comet and create alerts if the run exceeds thresholds.

Conclusion: The Shift is Permanent

The integration of DeepSeek with Cursor Agent Mode is more than just a new feature; it is a democratization of high-end AI coding. By lowering the barrier to entry (cost) and raising the ceiling of capability (reasoning), DeepSeek has empowered individual developers to possess the productivity of a small team.

For those not yet using this combination: update your Cursor client, grab a DeepSeek/ CometAPI API key, and switch on Agent Mode. The future of coding is here, and it is incredibly efficient.

Developers can access deepseek v3.2 through CometAPI now. To begin, explore the model capabilities of CometAPI in the Playground and consult the API guide for detailed instructions. Before accessing, please make sure you have logged in to CometAPI and obtained the API key. Com e tAPI offer a price far lower than the official price to help you integrate.

Ready to Go?→ Free trial of Deepseek v3.2!