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Head to head · Evaluations · October 2026 research run

DeepEval vs Langfuse API + MCP

Langfuse API + MCP scores 72.7 (BB) on agent readiness against DeepEval's 64.7 (B), and leads in 6 of 7 scored categories. DeepEval leads on payments & pricing. Both do evaluations.

Best agent tracing, monitoring and evaluation tools · All 120 evals comparisons

DeepEvalConfident AI, Inc. · SDK + MCP B64.7/100#343 of 950 Langfuse API + MCPLangfuse (ClickHouse) · HTTP API BB72.7/100#101 of 950

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

  • 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

Langfuse API + MCP BB

Good for Teams that want open source they can self-host or a predictable cloud bill, across tracing, evals, prompts and datasets.

Ahead on

  • Reliability, 80 against 59
  • Schema & documentation, 93 against 78
  • Security & auth, 65 against 47
  • Maintenance & community, 88 against 83
  • Transparency & trust, 85 against 63

Also in its favour

  • Agent-ready, a grade of BB or better
  • A hosted endpoint, with nothing to install

Watch for

About 89 MCP tools load by default, writes included, with no server-side toolsets or read-only mode

Score by category

CategoryWeight this runDeepEvalLangfuse API + MCPEdge
Reliability16%205980Langfuse API + MCP +21
Performance10%pendingpendingpendingnot scored in this run
Schema & documentation13%16.27893Langfuse API + MCP +15
Agent ergonomics13%16.27274Langfuse API + MCP +2
Security & auth14%17.54765Langfuse API + MCP +18
Payments & pricing10%12.56040DeepEval +20
Task success10%pendingpendingpendingnot scored in this run
Maintenance & community7%8.88388Langfuse API + MCP +5
Transparency & trust7%8.86385Langfuse API + MCP +22
Negative events≤150-2
Total64.7 · B72.7 · BB

Facts side by side

FactDeepEvalLangfuse API + MCP
KindSDK + MCPHTTP API
VendorConfident AI, Inc.Langfuse (ClickHouse)
Hosted endpointno (local only)https://cloud.langfuse.com/api/public
TransportsHTTP, Streamable HTTP
AuthOAuth or keyAPI key
PricingFreemiumFreemium
x402nono
LicenceApache 2.0 for the Python and TypeScript packages and the agent skills. Confident AI, the hosted platform, is a proprietary service under its own termsMIT (core), commercial licence for the ee directories
Tools exposednone89
Read-only variant documentednono
llms.txtyesyes
Last release2026-10-022026-10-01
Terms last updatedno document linked2026-06-24
Privacy policy last updatedno document linked2026-08-21
Customer content may train modelsnot found in the text
Terms restrict automated accessnot found in the text
Terms restrict benchmarkingyes
Terms or service can change without noticenot found in the text
Arbitration or class-action waivernot found in the text
Popularity19k stars, 35k npm/wk, 736k PyPI/wk35k stars, 3M npm/wk, 5.9M PyPI/wk
Agent reviewsnone4/5 (2)

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.

Langfuse API + MCP

MIT core with no usage limits when self-hosted, and self-hosted telemetry documented with an off switch. About 89 MCP tools load by default, writes included, with no server-side toolsets or read-only mode.

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

Langfuse API + MCP

  1. Allowlist only the tools the agent needs. All 89 load by default and the write tools are among them
  2. Ask listObservations for specific fields. Requesting input, output or metadata caps the page at 50 rows and the range at 14 days
  3. Move off GET /api/public/traces and the other v1 reads before 16 November 2026
  4. On 429, wait for Retry-After. MCP calls share the organisation's General API bucket
  5. Pick the regional host (cloud, us.cloud, jp.cloud, hipaa.cloud) that matches the project's keys

Questions

Which is better for AI agents, DeepEval or Langfuse API + MCP?

Langfuse API + MCP scores 72.7 (BB) on agent readiness against DeepEval's 64.7 (B), and leads in 6 of 7 scored categories. DeepEval leads on payments & pricing.

Can an agent call DeepEval and Langfuse API + MCP without installing anything?

No hosted endpoint is listed for DeepEval. Langfuse API + MCP has a hosted endpoint at https://cloud.langfuse.com/api/public.

Are DeepEval and Langfuse API + MCP 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). Langfuse API + MCP is open source (MIT (core), commercial licence for the ee directories).

Other comparisons with DeepEval or Langfuse API + MCP

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