# DeepEval vs LangWatch

> LangWatch and DeepEval score within a point of each other for evaluations, 65.5 and 64.7 out of 100. Prices, MCP, x402, uptime and agent notes side by side.

- Canonical: https://www.anchorterminal.com/compare/deepeval-vs-langwatch
- Markdown: https://www.anchorterminal.com/compare/deepeval-vs-langwatch.md (~2,750 tokens)
- Slim: https://www.anchorterminal.com/compare/deepeval-vs-langwatch.min.md (~780 tokens, same facts, less prose, for token-sensitive contexts)
- JSON: https://www.anchorterminal.com/compare/deepeval-vs-langwatch.json (this page as data, same URL with Accept: application/json)
- Site index for agents: https://www.anchorterminal.com/llms.txt (full text: https://www.anchorterminal.com/llms-full.txt)
- API: https://www.anchorterminal.com/api/v1/index.json
- Updated: 2026-10-09

LangWatch and DeepEval score within a point of each other on agent readiness, 65.5 (B) and 64.7 (B). DeepEval leads on reliability, agent ergonomics and payments & pricing. Both do evaluations.

- DeepEval: grade B, 64.7/100, rank #343 of 950. Markdown https://www.anchorterminal.com/tools/deepeval.md · JSON https://www.anchorterminal.com/api/v1/tools/deepeval.json
- LangWatch: grade B, 65.5/100, rank #318 of 950. Markdown https://www.anchorterminal.com/tools/langwatch.md · JSON https://www.anchorterminal.com/api/v1/tools/langwatch.json
- Best agent tracing, monitoring and evaluation tools: https://www.anchorterminal.com/best/agent-observability/index.md
- All 120 evals comparisons: https://www.anchorterminal.com/compare/agent-observability/index.md

## Which one, for what

### DeepEval (B)

Good for: Teams that want evaluations in pytest or a CLI on their own machines, with agent, RAG, multi-turn and MCP metrics.

Ahead on:
- Reliability, 59 against 53
- Agent ergonomics, 72 against 67
- Payments & pricing, 60 against 40

Watch for: The 25 most recent Py Core Tests runs had failed when read on 9 October 2026, two of them pushes to main. Issue #3372 of 26 September reports the same

### LangWatch (B)

Good for: Teams that want tracing, evaluations and simulated-user agent tests in one open-source product, hosted in the EU or self-hosted, and that drive it from a coding assistant through MCP or the CLI.

Ahead on:
- Schema & documentation, 87 against 78
- Security & auth, 71 against 47
- Maintenance & community, 90 against 83
- Transparency & trust, 75 against 63

Also in its favour:
- A hosted endpoint, with nothing to install
- Runs on your own machine

Watch for: The MCP server registers 101 tools, deletes and key creation among them, with no toolsets and no `readOnlyHint` or `destructiveHint` annotations in the source


## Score by category

| Category | Weight | DeepEval | LangWatch | Edge |
| --- | --- | --- | --- | --- |
| Reliability | 16% (20 this run) | 59 | 53 | DeepEval +6 |
| Performance | 10%, pending | pending | pending | not scored in this run |
| Schema & documentation | 13% (16.2 this run) | 78 | 87 | LangWatch +9 |
| Agent ergonomics | 13% (16.2 this run) | 72 | 67 | DeepEval +5 |
| Security & auth | 14% (17.5 this run) | 47 | 71 | LangWatch +24 |
| Payments & pricing | 10% (12.5 this run) | 60 | 40 | DeepEval +20 |
| Task success | 10%, pending | pending | pending | not scored in this run |
| Maintenance & community | 7% (8.8 this run) | 83 | 90 | LangWatch +7 |
| Transparency & trust | 7% (8.8 this run) | 63 | 75 | LangWatch +12 |
| Negative events | ≤15 | 0 | -2 | |
| **Total** | | **64.7 · B** | **65.5 · B** | |

## Facts side by side

| Fact | DeepEval | LangWatch |
| --- | --- | --- |
| Kind | SDK + MCP | HTTP API |
| Vendor | Confident AI, Inc. | Reasoning Engine B.V. (LangWatch) |
| Hosted endpoint | no (local only) | `https://app.langwatch.ai` |
| Transports |  | HTTP, Streamable HTTP, SSE (legacy), stdio |
| Auth | OAuth or key | OAuth or key |
| Pricing | Freemium | Freemium |
| Price for evaluations | not published | $0.0546 per 1M tokens |
| x402 | no | no |
| Licence | Apache 2.0 for the Python and TypeScript packages and the agent skills. Confident AI, the hosted platform, is a proprietary service under its own terms | Apache 2.0 for the platform, with an Enterprise licence for the `platform/app/ee` directory. The SDKs and the MCP server are MIT |
| Tools exposed | none | 101 |
| Read-only variant documented | no | no |
| llms.txt | yes | yes |
| Last release | 2026-10-02 | 2026-10-02 |
| Terms last updated | no document linked | 2026-09-22 |
| Privacy policy last updated | no document linked | 2026-09-29 |
| Customer content may train models |  | not found in the text |
| Terms restrict automated access |  | yes |
| Terms restrict benchmarking |  | not found in the text |
| Terms or service can change without notice |  | yes |
| Arbitration or class-action waiver |  | not found in the text |
| Popularity | 19k stars, 35k npm/wk, 736k PyPI/wk | 4.9k stars, 50k npm/wk, 87k PyPI/wk |

## Verdicts

**DeepEval.** DeepEval runs evaluations and tracing locally under Apache 2.0 with no account, and writes each test run to JSON or SQLite. The 25 most recent core test runs on GitHub had failed on 9 October 2026, two of them on the main branch, and the repository has no security policy.

**LangWatch.** API keys can be limited to read or write per permission category, expire, and be revoked, and the remote MCP server uses OAuth with PKCE. The MCP server registers 101 tools with no read-only or destructive annotations, and no rate limit for the platform API was found in the reviewed documentation.

## Before you call either

### DeepEval

1. Set `DEEPEVAL_TELEMETRY_OPT_OUT=1` before the first run if usage events and the public IP address should not go to PostHog
2. Set a judge model key such as `OPENAI_API_KEY`, or use the non-LLM metrics. Most metrics call an LLM judge and bill the owner's provider account
3. Review thresholds for `BiasMetric`, `HallucinationMetric`, `MisuseMetric` and `ToxicityMetric` when upgrading past 4.2.0. Higher scores now mean better
4. Read results from `.deepeval/.latest_run_full.json` or a `results_folder`. `deepeval inspect` opens a terminal interface meant for a person
5. Pass an existing key with `deepeval login --api-key` in CI. Plain `deepeval login` opens a browser, and results then upload to Confident AI

### LangWatch

1. Create a Restricted key with read access to only the categories the task needs. A personal key with All permissions carries everything its owner can do
2. Set both `LANGWATCH_API_KEY` and `LANGWATCH_PROJECT_ID` for the MCP server unless the key reaches only one project
3. Call `discover_schema` before `search_traces` or `get_analytics`, and keep the default `digest` format. `json` returns the full raw trace
4. Allowlist MCP tools in the client. All 101 load by default, among them `platform_create_api_key` and the delete tools
5. Follow `next_cursor` until it is null on list endpoints. A full page does not mean more rows exist

## Questions

### Which is better for AI agents, DeepEval or LangWatch?

LangWatch and DeepEval score within a point of each other on agent readiness, 65.5 (B) and 64.7 (B). DeepEval leads on reliability, agent ergonomics and payments & pricing.

### Can an agent call DeepEval and LangWatch without installing anything?

No hosted endpoint is listed for DeepEval. LangWatch has a hosted endpoint at https://app.langwatch.ai.

### Are DeepEval and LangWatch open source?

Yes. DeepEval is open source (Apache 2.0 for the Python and TypeScript packages and the agent skills. Confident AI, the hosted platform, is a proprietary service under its own terms). LangWatch is open source (Apache 2.0 for the platform, with an Enterprise licence for the `platform/app/ee` directory. The SDKs and the MCP server are MIT).


## For agents

- This comparison as JSON: https://www.anchorterminal.com/compare/deepeval-vs-langwatch.json, and with the fewest tokens: https://www.anchorterminal.com/compare/deepeval-vs-langwatch.min.md
- Over MCP at https://www.anchorterminal.com/mcp (no key): `compare_tools {"a": "deepeval", "b": "langwatch"}`. From a terminal: `anchor compare deepeval langwatch`
- Each listing in full: https://www.anchorterminal.com/api/v1/tools/deepeval.json and https://www.anchorterminal.com/api/v1/tools/langwatch.json

## Other comparisons with DeepEval or LangWatch

- [Arize Phoenix vs DeepEval](https://www.anchorterminal.com/compare/arize-phoenix-vs-deepeval.md)
- [Arize Phoenix vs LangWatch](https://www.anchorterminal.com/compare/arize-phoenix-vs-langwatch.md)
- [Baserun vs DeepEval](https://www.anchorterminal.com/compare/baserun-vs-deepeval.md)
- [Baserun vs LangWatch](https://www.anchorterminal.com/compare/baserun-vs-langwatch.md)
- [Braintrust API + MCP vs DeepEval](https://www.anchorterminal.com/compare/braintrust-vs-deepeval.md)
- [Braintrust API + MCP vs LangWatch](https://www.anchorterminal.com/compare/braintrust-vs-langwatch.md)
- [Galileo API + MCP vs LangWatch](https://www.anchorterminal.com/compare/galileo-vs-langwatch.md)
- [Helicone AI Gateway + MCP vs LangWatch](https://www.anchorterminal.com/compare/helicone-vs-langwatch.md)
- [HoneyHive vs LangWatch](https://www.anchorterminal.com/compare/honeyhive-vs-langwatch.md)
- [Laminar API + MCP vs LangWatch](https://www.anchorterminal.com/compare/laminar-vs-langwatch.md)
- [Langfuse API + MCP vs LangWatch](https://www.anchorterminal.com/compare/langfuse-vs-langwatch.md)
- [LangSmith API + MCP vs LangWatch](https://www.anchorterminal.com/compare/langsmith-vs-langwatch.md)
- [LangWatch vs MLflow Tracing](https://www.anchorterminal.com/compare/langwatch-vs-mlflow-tracing.md)
- [LangWatch vs Prefactor](https://www.anchorterminal.com/compare/langwatch-vs-prefactor.md)
- [LangWatch vs Pydantic Logfire](https://www.anchorterminal.com/compare/langwatch-vs-pydantic-logfire.md)
- [LangWatch vs Respan API + MCP](https://www.anchorterminal.com/compare/langwatch-vs-respan.md)
- [LangWatch vs W&B Weave](https://www.anchorterminal.com/compare/langwatch-vs-wandb-weave.md)
- [DeepEval vs Galileo API + MCP](https://www.anchorterminal.com/compare/deepeval-vs-galileo.md)
- [DeepEval vs Helicone AI Gateway + MCP](https://www.anchorterminal.com/compare/deepeval-vs-helicone.md)
- [DeepEval vs HoneyHive](https://www.anchorterminal.com/compare/deepeval-vs-honeyhive.md)
- [DeepEval vs Laminar API + MCP](https://www.anchorterminal.com/compare/deepeval-vs-laminar.md)
- [DeepEval vs Langfuse API + MCP](https://www.anchorterminal.com/compare/deepeval-vs-langfuse.md)
- [DeepEval vs LangSmith API + MCP](https://www.anchorterminal.com/compare/deepeval-vs-langsmith.md)
- [DeepEval vs MLflow Tracing](https://www.anchorterminal.com/compare/deepeval-vs-mlflow-tracing.md)
- [DeepEval vs Prefactor](https://www.anchorterminal.com/compare/deepeval-vs-prefactor.md)
- [DeepEval vs Pydantic Logfire](https://www.anchorterminal.com/compare/deepeval-vs-pydantic-logfire.md)
- [DeepEval vs Respan API + MCP](https://www.anchorterminal.com/compare/deepeval-vs-respan.md)
- [DeepEval vs W&B Weave](https://www.anchorterminal.com/compare/deepeval-vs-wandb-weave.md)