{
  "data": {
    "a": {
      "slug": "deepeval",
      "name": "DeepEval",
      "vendor": "Confident AI, Inc.",
      "vendorUrl": "https://www.confident-ai.com",
      "kind": "sdk",
      "category": "agent-observability",
      "summary": "DeepEval is an open-source Python and TypeScript framework from Confident AI for evaluating LLM applications and agents. Evaluations run locally through a pytest plugin and the `deepeval` CLI, with optional reporting to the hosted Confident AI platform.",
      "url": "https://www.anchorterminal.com/tools/deepeval",
      "markdownUrl": "https://www.anchorterminal.com/tools/deepeval.md",
      "slimMarkdownUrl": "https://www.anchorterminal.com/tools/deepeval.min.md",
      "jsonUrl": "https://www.anchorterminal.com/api/v1/tools/deepeval.json",
      "repo": "https://github.com/confident-ai/deepeval",
      "license": "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",
      "transports": [],
      "packages": [
        {
          "registry": "pypi",
          "name": "deepeval"
        },
        {
          "registry": "npm",
          "name": "deepeval"
        }
      ],
      "auth": "mixed",
      "authNotes": "No credential is needed to run evaluations locally. Most metrics call an LLM judge, so the owner supplies a model provider key such as `OPENAI_API_KEY` in the environment or a dotenv file. Reporting to Confident AI needs a project API key in `CONFIDENT_API_KEY`. `deepeval login` pairs with a browser through a device code and writes the key to `.env.local`, and `deepeval login --api-key` takes an existing key for CI. Confident AI project keys are named, take an expiry, and can be deactivated, rotated with a grace period or deleted. No per-permission scopes for project keys were found in the page read.",
      "pricing": "freemium",
      "pricingNotes": "DeepEval is free under Apache 2.0 and runs without an account. LLM judge calls are billed by the owner's model provider. The hosted Confident AI platform has a Free plan with no card (5 test runs a week, 2 seats, 1 project, 1 GB-month of trace spans), Starter at $200 a month, Team at $2,000 a month, both with $1 per GB-month beyond the included trace spans, and Enterprise by quote (https://www.confident-ai.com/pricing).",
      "priceSummary": "$200 / mo",
      "where": "local",
      "x402": {
        "level": "no",
        "evidence": "No x402, MPP or L402 in the repository docs, the Confident AI docs index or the pricing page (checked 2026-10-09).",
        "endpoints": []
      },
      "toolCount": null,
      "popularity": {
        "githubStars": 18700,
        "npmWeekly": 35092,
        "pypiWeekly": 735637,
        "asOf": "2026-10-09"
      },
      "docsUrl": "https://deepeval.com/docs/getting-started",
      "llmsTxt": "https://deepeval.com/llms.txt",
      "capabilities": [
        "obs.evals",
        "obs.traces",
        "obs.datasets",
        "obs.prompts"
      ],
      "tags": [
        "open-source",
        "apache-2.0",
        "local",
        "cli",
        "python",
        "typescript",
        "pytest",
        "llms-txt",
        "agent-skills",
        "opentelemetry",
        "freemium",
        "no-card"
      ],
      "lastRelease": "2026-10-02",
      "graded": true,
      "anchor": {
        "graded": true,
        "score": 64.7,
        "grade": "B",
        "agentReady": false,
        "rank": 343,
        "ranked": true,
        "rankOf": 950,
        "categoryRank": 9,
        "methodology": "0.4",
        "run": "2026-10-01",
        "scores": {
          "ergonomics": 72,
          "maintenance": 83,
          "payments": 60,
          "reliability": 59,
          "schema": 78,
          "security": 47,
          "transparency": 63
        },
        "pending": [
          "performance",
          "tasks"
        ],
        "assessment": {
          "confidence": "medium",
          "date": "2026-10-09"
        },
        "negative": 0,
        "verdict": "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.",
        "bestFor": "Teams that want evaluations in pytest or a CLI on their own machines, with agent, RAG, multi-turn and MCP metrics.",
        "strengths": [
          "Apache-2.0 framework that runs evaluations and tracing locally with no account. Test runs are written to JSON files or a SQLite database on the owner's disk",
          "Python 4.2.8 was tagged on 2 October 2026, with 14 Python releases tagged since 9 August and TypeScript 0.9.21 on 30 September",
          "`deepeval test run` takes flags for parallel processes, repeats, a result cache, ignoring errors and skipping cases with missing parameters",
          "llms.txt on deepeval.com, three agent skills in the repository and plugin manifests for Claude Code and Cursor",
          "Telemetry goes only to PostHog per the docs and the source, and `DEEPEVAL_TELEMETRY_OPT_OUT=1` turns it off"
        ],
        "weaknesses": [
          "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",
          "No SECURITY.md, no published advisories and no security.txt on deepeval.com or confident-ai.com. The trust centre is drawn by script and was not read",
          "Release 4.2.0 reversed the score direction of four safety metrics in a minor version. The changelog marks it as breaking and the code warns at run time",
          "The 2026 changelog stops at 4.2.0 of 25 August. Releases 4.2.1 to 4.2.8 have no entries in it",
          "Usage telemetry is on by default and sends the public IP address. The source also sends the judge model, runtime kind and CLI command, which the docs list omits",
          "Confident AI's terms forbid using its services for competitive analysis. This matters before any probe of the hosted platform is run"
        ],
        "agentNotes": [
          "Set `DEEPEVAL_TELEMETRY_OPT_OUT=1` before the first run if usage events and the public IP address should not go to PostHog",
          "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",
          "Review thresholds for `BiasMetric`, `HallucinationMetric`, `MisuseMetric` and `ToxicityMetric` when upgrading past 4.2.0. Higher scores now mean better",
          "Read results from `.deepeval/.latest_run_full.json` or a `results_folder`. `deepeval inspect` opens a terminal interface meant for a person",
          "Pass an existing key with `deepeval login --api-key` in CI. Plain `deepeval login` opens a browser, and results then upload to Confident AI"
        ],
        "metrics": {
          "kind": "local",
          "measured": false
        },
        "reviewCount": 0,
        "avgRating": 0,
        "history": [
          {
            "basis": "public evidence",
            "confidence": "medium",
            "grade": "B",
            "methodology": "0.4",
            "pending": [
              "performance",
              "tasks"
            ],
            "run": "2026-10-01",
            "runLabel": "October 2026 research run",
            "score": 64.7
          }
        ],
        "editorialScores": {
          "ergonomics": 72,
          "maintenance": 83,
          "payments": 60,
          "reliability": 59,
          "schema": 78,
          "security": 47,
          "transparency": 73
        },
        "provenanceScore": 52
      },
      "connect": {
        "install": "pip install -U deepeval"
      },
      "letme": {
        "capability": "https://letme.dev/obs.evals",
        "tool": "https://letme.dev/deepeval"
      },
      "area": "developer",
      "unitPrices": [
        {
          "item": "Confident AI Starter plan",
          "unit": "month",
          "usd": 200,
          "note": "Hosted platform, optional. Unlimited seats, 5 projects, 5 GB-months of trace spans"
        },
        {
          "item": "Confident AI Team plan",
          "unit": "month",
          "usd": 2000,
          "note": "Hosted platform, optional. Unlimited projects, 75 GB-months of trace spans"
        },
        {
          "item": "Confident AI trace spans beyond the plan",
          "unit": "gb-month",
          "usd": 1,
          "note": "Per GB-month ingested or retained on Starter and Team"
        }
      ],
      "provenance": {
        "legalEntity": "Confident AI, Inc.",
        "domain": "confident-ai.com",
        "domainRegistered": "2023-08-15",
        "endpointOnVendorDomain": true,
        "terms": "",
        "privacy": "",
        "statusPage": "",
        "changelog": "https://deepeval.com/changelog",
        "securityTxt": "none",
        "checked": "2026-10-09",
        "notes": [
          "DeepEval is software the owner runs under the Apache-2.0 licence, which stands in for terms here. Confident AI's Terms of Service (https://www.confident-ai.com/terms) and privacy policy (https://www.confident-ai.com/privacy-policy) govern only the optional hosted platform that `deepeval login`, `view` and `gate` use, so they are not linked as this listing's terms.",
          "The Terms of Service (last modified 2 March 2026) name Confident AI, Inc., a Delaware corporation, with offices at 33rd 8th St, San Francisco, CA 94103, as printed on the page.",
          "The privacy policy (last modified 26 May 2026) says it does not apply to Customer Data, which Confident AI processes under its data processing agreement. A DPA and a sub-processor list are published at /dpa and /subprocessors-list.",
          "When logged in, DeepEval sends results to api.confident-ai.com or eu.api.confident-ai.com and traces to otel.confident-ai.com, all on the vendor's domain. Telemetry goes to us.i.posthog.com.",
          "https://www.confident-ai.com/.well-known/security.txt and https://deepeval.com/.well-known/security.txt both answered 404.",
          "No status page link was found on the pages read. The trust centre at trust.oneleet.com/confident-ai is drawn by script and was not read.",
          "RDAP gives 2023-08-15 as the registration date of confident-ai.com and 2023-07-15 for deepeval.com, both through NameCheap, Inc."
        ],
        "score": 52
      },
      "pageJsonUrl": "https://www.anchorterminal.com/tools/deepeval.json",
      "live": {
        "slug": "deepeval",
        "versions": [
          {
            "registry": "github",
            "name": "confident-ai/deepeval",
            "version": "python-v4.2.4",
            "released": "2026-09-22",
            "seenAt": "2026-10-09T16:48:57.205584437Z"
          },
          {
            "registry": "npm",
            "name": "deepeval",
            "version": "0.9.22",
            "seenAt": "2026-10-09T16:48:56.771405961Z"
          },
          {
            "registry": "pypi",
            "name": "deepeval",
            "version": "4.2.8",
            "released": "2026-10-02",
            "seenAt": "2026-10-09T16:48:56.555388028Z"
          }
        ],
        "githubStars": 18722,
        "npmWeekly": 35092,
        "pypiWeekly": 735637,
        "pages": [
          {
            "url": "https://deepeval.com/changelog",
            "kind": "changelog",
            "status": 200,
            "checkedAt": "2026-10-09T18:34:45.297656608Z",
            "changedAt": "0001-01-01T00:00:00Z",
            "fingerprint": "5c04fa001f0e"
          },
          {
            "url": "https://www.confident-ai.com/pricing",
            "kind": "pricing",
            "status": 200,
            "checkedAt": "2026-10-09T18:49:15.052218782Z",
            "changedAt": "0001-01-01T00:00:00Z",
            "fingerprint": "f37a25bd3065"
          }
        ],
        "updatedAt": "2026-10-09T18:49:15.052218782Z"
      }
    },
    "answer": "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 \u0026 pricing.",
    "b": {
      "slug": "langwatch",
      "name": "LangWatch",
      "vendor": "Reasoning Engine B.V. (LangWatch)",
      "vendorUrl": "https://langwatch.ai",
      "kind": "http-api",
      "category": "agent-observability",
      "summary": "LangWatch is an open-source platform for tracing, evaluating and testing LLM applications and agents, with prompt management, datasets and an AI gateway. It runs hosted or self-hosted, with a REST API, SDKs, a CLI and an MCP server.",
      "url": "https://www.anchorterminal.com/tools/langwatch",
      "markdownUrl": "https://www.anchorterminal.com/tools/langwatch.md",
      "slimMarkdownUrl": "https://www.anchorterminal.com/tools/langwatch.min.md",
      "jsonUrl": "https://www.anchorterminal.com/api/v1/tools/langwatch.json",
      "repo": "https://github.com/langwatch/langwatch",
      "license": "Apache 2.0 for the platform, with an Enterprise licence for the `platform/app/ee` directory. The SDKs and the MCP server are MIT",
      "transports": [
        "http",
        "streamable-http",
        "sse",
        "stdio"
      ],
      "remoteUrl": "https://app.langwatch.ai",
      "packages": [
        {
          "registry": "npm",
          "name": "langwatch"
        },
        {
          "registry": "npm",
          "name": "@langwatch/mcp-server"
        },
        {
          "registry": "pypi",
          "name": "langwatch"
        }
      ],
      "auth": "mixed",
      "authNotes": "A person signs up at app.langwatch.ai and creates keys under Settings, API Keys, with no review step. API keys (`sk-lw-`) go in `X-Auth-Token` or as a Bearer token. A personal key never exceeds its owner's permissions, a service key belongs to the organisation and only admins create one. Either can be All or Restricted to read or write per permission category, scoped to projects, teams or the organisation, given an expiry and revoked. Ingestion keys (`ik-lw-`) can only write traces to one project. The remote MCP server uses OAuth authorisation code with PKCE and dynamic client registration. The CLI logs in with a device code approved in a browser.",
      "pricing": "freemium",
      "pricingNotes": "The Developer plan is free with no card and includes 50,000 events a month, 2 users and 3 scenarios, so an agent can start without a contract once a person has signed up. Growth is 29 euros per core seat a month with 200,000 events, then 5 euros per 100,000 events and 3 euros per GB kept beyond the included retention. Enterprise is sold through sales. Instant Evals cost $0.0546 per million input tokens, with a $1 budget on unpaid organisations. The pricing page has a currency switch and we read the euro prices only. Self-hosting under Apache 2.0 is free with no volume cap, and an Enterprise licence is priced per seat (https://langwatch.ai/pricing, https://langwatch.ai/docs/pricing.md).",
      "priceSummary": "Freemium",
      "where": "both",
      "x402": {
        "level": "no",
        "evidence": "No x402, MPP or L402 in the docs index, the OpenAPI document or the pricing page (checked 2026-10-09).",
        "endpoints": []
      },
      "toolCount": 101,
      "popularity": {
        "githubStars": 4925,
        "npmWeekly": 50105,
        "pypiWeekly": 87325,
        "asOf": "2026-10-09"
      },
      "docsUrl": "https://langwatch.ai/docs/introduction",
      "llmsTxt": "https://langwatch.ai/docs/llms.txt",
      "openapi": "https://app.langwatch.ai/api/gateway/v1/openapi.json",
      "capabilities": [
        "obs.traces",
        "obs.evals",
        "obs.prompts",
        "obs.datasets",
        "obs.gateway"
      ],
      "tags": [
        "hosted",
        "freemium",
        "no-card",
        "open-source",
        "self-hosted",
        "mcp",
        "oauth",
        "llms-txt",
        "openapi",
        "opentelemetry",
        "python",
        "typescript",
        "go",
        "cli",
        "status-page",
        "eu-hosted"
      ],
      "lastRelease": "2026-10-02",
      "graded": true,
      "anchor": {
        "graded": true,
        "score": 65.5,
        "grade": "B",
        "agentReady": false,
        "rank": 318,
        "ranked": true,
        "rankOf": 950,
        "categoryRank": 7,
        "methodology": "0.4",
        "run": "2026-10-01",
        "scores": {
          "ergonomics": 67,
          "maintenance": 90,
          "payments": 40,
          "reliability": 53,
          "schema": 87,
          "security": 71,
          "transparency": 75
        },
        "pending": [
          "performance",
          "tasks"
        ],
        "assessment": {
          "confidence": "medium",
          "date": "2026-10-09"
        },
        "negative": -2,
        "negativeNotes": [
          "2026-08-19. Advisory GHSA-h25p-f8f6-2ccf, rated moderate. The standalone HTTP mode of `@langwatch/mcp-server` 0.7.0 to 1.0.0 authorised requests by session id alone and accepted an API key in the URL. Fixed in 2.0.0 on 7 August 2026 and flagged as a breaking change. The advisory says the default stdio mode and the hosted handler were never affected, so -2 (https://github.com/langwatch/langwatch/security/advisories/GHSA-h25p-f8f6-2ccf)"
        ],
        "verdict": "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.",
        "bestFor": "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.",
        "strengths": [
          "API keys take read or write per permission category, a project, team or organisation scope and an expiry. Ingestion keys can only write traces",
          "A public OpenAPI 3.1 document covers 328 operations and is served without a key, with llms.txt and a Markdown twin of every docs page",
          "Apache 2.0 platform with MIT SDKs and MCP server. Self-hosting has no volume cap, and every outbound call is documented with its off switch",
          "The free Developer plan needs no card and includes 50,000 events a month. Paid usage is published at 5 euros per 100,000 events",
          "Platform 3.20.1 shipped on 2 October 2026, with 21 platform releases dated since 11 July in the repository changelog"
        ],
        "weaknesses": [
          "The MCP server registers 101 tools, deletes and key creation among them, with no toolsets and no `readOnlyHint` or `destructiveHint` annotations in the source",
          "No request rate limit for the platform API was found in the reviewed documentation. Only two operations in the OpenAPI document declare a 429",
          "The status page shows Scenarios down for 9 hours 34 minutes on 8 September 2026 and trace processing degraded for 14 hours 44 minutes on 31 July",
          "The Terms of Service of 22 September 2026 say users will not access the platform through automated or non-human means, which the API and MCP server contradict",
          "The audit log is Enterprise only and records neither sign-ins nor reads of traces"
        ],
        "agentNotes": [
          "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",
          "Set both `LANGWATCH_API_KEY` and `LANGWATCH_PROJECT_ID` for the MCP server unless the key reaches only one project",
          "Call `discover_schema` before `search_traces` or `get_analytics`, and keep the default `digest` format. `json` returns the full raw trace",
          "Allowlist MCP tools in the client. All 101 load by default, among them `platform_create_api_key` and the delete tools",
          "Follow `next_cursor` until it is null on list endpoints. A full page does not mean more rows exist"
        ],
        "metrics": {
          "kind": "remote",
          "measured": false
        },
        "reviewCount": 0,
        "avgRating": 0,
        "history": [
          {
            "basis": "public evidence",
            "confidence": "medium",
            "grade": "B",
            "methodology": "0.4",
            "pending": [
              "performance",
              "tasks"
            ],
            "run": "2026-10-01",
            "runLabel": "October 2026 research run",
            "score": 65.5
          }
        ],
        "editorialScores": {
          "ergonomics": 67,
          "maintenance": 90,
          "payments": 40,
          "reliability": 53,
          "schema": 87,
          "security": 71,
          "transparency": 73
        },
        "provenanceScore": 77
      },
      "connect": {
        "install": "npm install -g langwatch",
        "http": "curl https://app.langwatch.ai/api/gateway/v1/openapi.json",
        "claudeCode": "claude mcp add langwatch --env LANGWATCH_API_KEY=sk-lw-... --env LANGWATCH_PROJECT_ID=your-project-id -- npx -y @langwatch/mcp-server",
        "config": {
          "mcpServers": {
            "langwatch": {
              "args": [
                "-y",
                "@langwatch/mcp-server"
              ],
              "command": "npx",
              "env": {
                "LANGWATCH_API_KEY": "sk-lw-...",
                "LANGWATCH_PROJECT_ID": "your-project-id"
              }
            }
          }
        }
      },
      "letme": {
        "capability": "https://letme.dev/obs.traces",
        "tool": "https://letme.dev/langwatch"
      },
      "area": "developer",
      "unitPrices": [
        {
          "item": "Instant Evals, judge input tokens",
          "unit": "1m-tokens",
          "usd": 0.0546,
          "note": "Output is free. Unpaid organisations have a $1 budget in total"
        }
      ],
      "provenance": {
        "legalEntity": "Reasoning Engine B.V. (doing business as LangWatch)",
        "domain": "langwatch.ai",
        "domainRegistered": "2023-09-17",
        "endpointOnVendorDomain": true,
        "terms": "https://langwatch.ai/legal/terms-conditions",
        "privacy": "https://langwatch.ai/legal/privacy-policy",
        "statusPage": "https://status.langwatch.ai",
        "changelog": "https://langwatch.ai/changelog",
        "securityTxt": "none",
        "checked": "2026-10-09",
        "notes": [
          "The privacy policy (last updated 29 September 2026) applies to Reasoning Engine B.V., doing business as LangWatch, and covers the website and the Cloud Service. The Terms of Service (last updated 22 September 2026) cover the platform and the on-premise product.",
          "The terms page names the entity as Reasoning Engines B.V. in its heading and Reasoning Engine B.V. in its definitions, gives Singel 126, Amsterdam as the registered office and Herengracht 551, Amsterdam as the contact address. The site footer reads LangWatch B.V.",
          "The API, the hosted MCP server and the OpenAPI document are served from app.langwatch.ai. Hosted services for self-hosted installs with a licence use connect.langwatch.ai and gateway.langwatch.ai.",
          "https://langwatch.ai/.well-known/security.txt returns the website's HTML shell, not a security.txt file. SECURITY.md in the repository gives security@langwatch.ai and GitHub private reporting.",
          "RDAP for langwatch.ai gives a registration date of 2023-09-17 and GoDaddy.com, LLC as registrar.",
          "The trust report and sub-processor list are on app.eu.vanta.com, whose robots.txt disallows every path, so we did not read them."
        ],
        "score": 77
      },
      "pageJsonUrl": "https://www.anchorterminal.com/tools/langwatch.json",
      "live": {
        "slug": "langwatch",
        "probe": {
          "target": "https://app.langwatch.ai",
          "method": "get",
          "lastAt": "2026-10-10T02:07:13.765114436Z",
          "lastOk": true,
          "lastStatus": 200,
          "lastMs": 67,
          "authRequired": false,
          "uptime24h": 100,
          "uptime30d": 100,
          "p50ms24h": 91,
          "p95ms24h": 160,
          "samples24h": 191,
          "samples30d": 191,
          "days": [
            {
              "date": "2026-10-09",
              "probes": 169,
              "ok": 169
            },
            {
              "date": "2026-10-10",
              "probes": 22,
              "ok": 22
            }
          ]
        },
        "vendorStatus": {
          "page": "https://status.langwatch.ai",
          "indicator": "unknown",
          "summary": "no machine-readable status found",
          "checkedAt": "2026-10-10T00:50:45.203628525Z"
        },
        "versions": [
          {
            "registry": "github",
            "name": "langwatch/langwatch",
            "version": "langwatch-3.20.1",
            "released": "2026-10-02",
            "seenAt": "2026-10-09T17:01:41.038363513Z"
          },
          {
            "registry": "npm",
            "name": "@langwatch/mcp-server",
            "version": "2.1.0",
            "seenAt": "2026-10-09T17:01:39.446290411Z"
          },
          {
            "registry": "npm",
            "name": "langwatch",
            "version": "1.19.0",
            "seenAt": "2026-10-09T17:01:38.618750656Z"
          },
          {
            "registry": "pypi",
            "name": "langwatch",
            "version": "1.4.0",
            "released": "2026-09-06",
            "seenAt": "2026-10-09T17:01:40.840754661Z"
          }
        ],
        "githubStars": 4927,
        "npmWeekly": 40157,
        "pypiWeekly": 90049,
        "securityTxt": {
          "url": "https://langwatch.ai/.well-known/security.txt",
          "state": "none",
          "checkedAt": "2026-10-09T15:40:17.627005627Z"
        },
        "llmsTxt": {
          "url": "https://langwatch.ai/docs/llms.txt",
          "ok": true,
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        "updatedAt": "2026-10-10T02:07:13.765114436Z"
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    "facts": [
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        "b": "HTTP API",
        "name": "Kind"
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      {
        "a": "Confident AI, Inc.",
        "b": "Reasoning Engine B.V. (LangWatch)",
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      {
        "a": "no (local only)",
        "b": "https://app.langwatch.ai",
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        "b": "not found in the text",
        "name": "Arbitration or class-action waiver"
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        "a": "19k stars, 35k npm/wk, 736k PyPI/wk",
        "b": "4.9k stars, 50k npm/wk, 87k PyPI/wk",
        "name": "Popularity"
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    ],
    "faq": [
      {
        "answer": "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 \u0026 pricing.",
        "question": "Which is better for AI agents, DeepEval or LangWatch?"
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      {
        "answer": "No hosted endpoint is listed for DeepEval. LangWatch has a hosted endpoint at https://app.langwatch.ai.",
        "question": "Can an agent call DeepEval and LangWatch without installing anything?"
      },
      {
        "answer": "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).",
        "question": "Are DeepEval and LangWatch open source?"
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    "goodFor": [
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        "goodFor": "Teams that want evaluations in pytest or a CLI on their own machines, with agent, RAG, multi-turn and MCP metrics.",
        "slug": "deepeval",
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          "Schema \u0026 documentation, 87 against 78",
          "Security \u0026 auth, 71 against 47",
          "Maintenance \u0026 community, 90 against 83",
          "Transparency \u0026 trust, 75 against 63"
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          "A hosted endpoint, with nothing to install",
          "Runs on your own machine"
        ],
        "goodFor": "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.",
        "slug": "langwatch",
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        "json": "https://www.anchorterminal.com/compare/baserun-vs-deepeval.json",
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      {
        "json": "https://www.anchorterminal.com/compare/braintrust-vs-deepeval.json",
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        "json": "https://www.anchorterminal.com/compare/galileo-vs-langwatch.json",
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        "json": "https://www.anchorterminal.com/compare/langwatch-vs-respan.json",
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        "json": "https://www.anchorterminal.com/compare/langwatch-vs-wandb-weave.json",
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        "json": "https://www.anchorterminal.com/compare/deepeval-vs-galileo.json",
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        "json": "https://www.anchorterminal.com/compare/deepeval-vs-helicone.json",
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        "url": "https://www.anchorterminal.com/compare/deepeval-vs-helicone"
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        "json": "https://www.anchorterminal.com/compare/deepeval-vs-honeyhive.json",
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        "url": "https://www.anchorterminal.com/compare/deepeval-vs-honeyhive"
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        "json": "https://www.anchorterminal.com/compare/deepeval-vs-laminar.json",
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        "url": "https://www.anchorterminal.com/compare/deepeval-vs-wandb-weave"
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    "scores": [
      {
        "by": 6,
        "deepeval": 59,
        "edge": "deepeval",
        "key": "reliability",
        "langwatch": 53,
        "name": "Reliability",
        "weight": 16
      },
      {
        "key": "performance",
        "name": "Performance",
        "pending": true,
        "weight": 10
      },
      {
        "by": 9,
        "deepeval": 78,
        "edge": "langwatch",
        "key": "schema",
        "langwatch": 87,
        "name": "Schema \u0026 documentation",
        "weight": 13
      },
      {
        "by": 5,
        "deepeval": 72,
        "edge": "deepeval",
        "key": "ergonomics",
        "langwatch": 67,
        "name": "Agent ergonomics",
        "weight": 13
      },
      {
        "by": 24,
        "deepeval": 47,
        "edge": "langwatch",
        "key": "security",
        "langwatch": 71,
        "name": "Security \u0026 auth",
        "weight": 14
      },
      {
        "by": 20,
        "deepeval": 60,
        "edge": "deepeval",
        "key": "payments",
        "langwatch": 40,
        "name": "Payments \u0026 pricing",
        "weight": 10
      },
      {
        "key": "tasks",
        "name": "Task success",
        "pending": true,
        "weight": 10
      },
      {
        "by": 7,
        "deepeval": 83,
        "edge": "langwatch",
        "key": "maintenance",
        "langwatch": 90,
        "name": "Maintenance \u0026 community",
        "weight": 7
      },
      {
        "by": 12,
        "deepeval": 63,
        "edge": "langwatch",
        "key": "transparency",
        "langwatch": 75,
        "name": "Transparency \u0026 trust",
        "weight": 7
      }
    ],
    "summary": "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 \u0026 pricing. Both do evaluations.",
    "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."
    }
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  "markdown": "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 \u0026 pricing. Both do evaluations.\n\n- 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\n- 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\n- Best agent tracing, monitoring and evaluation tools: https://www.anchorterminal.com/best/agent-observability/index.md\n- All 120 evals comparisons: https://www.anchorterminal.com/compare/agent-observability/index.md\n\n## Which one, for what\n\n### DeepEval (B)\n\nGood for: Teams that want evaluations in pytest or a CLI on their own machines, with agent, RAG, multi-turn and MCP metrics.\n\nAhead on:\n- Reliability, 59 against 53\n- Agent ergonomics, 72 against 67\n- Payments \u0026 pricing, 60 against 40\n\nWatch 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\n\n### LangWatch (B)\n\nGood 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.\n\nAhead on:\n- Schema \u0026 documentation, 87 against 78\n- Security \u0026 auth, 71 against 47\n- Maintenance \u0026 community, 90 against 83\n- Transparency \u0026 trust, 75 against 63\n\nAlso in its favour:\n- A hosted endpoint, with nothing to install\n- Runs on your own machine\n\nWatch 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\n\n\n## Score by category\n\n| Category | Weight | DeepEval | LangWatch | Edge |\n| --- | --- | --- | --- | --- |\n| Reliability | 16% (20 this run) | 59 | 53 | DeepEval +6 |\n| Performance | 10%, pending | pending | pending | not scored in this run |\n| Schema \u0026 documentation | 13% (16.2 this run) | 78 | 87 | LangWatch +9 |\n| Agent ergonomics | 13% (16.2 this run) | 72 | 67 | DeepEval +5 |\n| Security \u0026 auth | 14% (17.5 this run) | 47 | 71 | LangWatch +24 |\n| Payments \u0026 pricing | 10% (12.5 this run) | 60 | 40 | DeepEval +20 |\n| Task success | 10%, pending | pending | pending | not scored in this run |\n| Maintenance \u0026 community | 7% (8.8 this run) | 83 | 90 | LangWatch +7 |\n| Transparency \u0026 trust | 7% (8.8 this run) | 63 | 75 | LangWatch +12 |\n| Negative events | ≤15 | 0 | -2 | |\n| **Total** | | **64.7 · B** | **65.5 · B** | |\n\n## Facts side by side\n\n| Fact | DeepEval | LangWatch |\n| --- | --- | --- |\n| Kind | SDK + MCP | HTTP API |\n| Vendor | Confident AI, Inc. | Reasoning Engine B.V. (LangWatch) |\n| Hosted endpoint | no (local only) | `https://app.langwatch.ai` |\n| Transports |  | HTTP, Streamable HTTP, SSE (legacy), stdio |\n| Auth | OAuth or key | OAuth or key |\n| Pricing | Freemium | Freemium |\n| Price for evaluations | not published | $0.0546 per 1M tokens |\n| x402 | no | no |\n| 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 |\n| Tools exposed | none | 101 |\n| Read-only variant documented | no | no |\n| llms.txt | yes | yes |\n| Last release | 2026-10-02 | 2026-10-02 |\n| Terms last updated | no document linked | 2026-09-22 |\n| Privacy policy last updated | no document linked | 2026-09-29 |\n| Customer content may train models |  | not found in the text |\n| Terms restrict automated access |  | yes |\n| Terms restrict benchmarking |  | not found in the text |\n| Terms or service can change without notice |  | yes |\n| Arbitration or class-action waiver |  | not found in the text |\n| Popularity | 19k stars, 35k npm/wk, 736k PyPI/wk | 4.9k stars, 50k npm/wk, 87k PyPI/wk |\n\n## Verdicts\n\n**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.\n\n**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.\n\n## Before you call either\n\n### DeepEval\n\n1. Set `DEEPEVAL_TELEMETRY_OPT_OUT=1` before the first run if usage events and the public IP address should not go to PostHog\n2. 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\n3. Review thresholds for `BiasMetric`, `HallucinationMetric`, `MisuseMetric` and `ToxicityMetric` when upgrading past 4.2.0. Higher scores now mean better\n4. Read results from `.deepeval/.latest_run_full.json` or a `results_folder`. `deepeval inspect` opens a terminal interface meant for a person\n5. Pass an existing key with `deepeval login --api-key` in CI. Plain `deepeval login` opens a browser, and results then upload to Confident AI\n\n### LangWatch\n\n1. 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\n2. Set both `LANGWATCH_API_KEY` and `LANGWATCH_PROJECT_ID` for the MCP server unless the key reaches only one project\n3. Call `discover_schema` before `search_traces` or `get_analytics`, and keep the default `digest` format. `json` returns the full raw trace\n4. Allowlist MCP tools in the client. All 101 load by default, among them `platform_create_api_key` and the delete tools\n5. Follow `next_cursor` until it is null on list endpoints. A full page does not mean more rows exist\n\n## Questions\n\n### Which is better for AI agents, DeepEval or LangWatch?\n\nLangWatch 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 \u0026 pricing.\n\n### Can an agent call DeepEval and LangWatch without installing anything?\n\nNo hosted endpoint is listed for DeepEval. LangWatch has a hosted endpoint at https://app.langwatch.ai.\n\n### Are DeepEval and LangWatch open source?\n\nYes. 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).\n\n\n## For agents\n\n- 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\n- Over MCP at https://www.anchorterminal.com/mcp (no key): `compare_tools {\"a\": \"deepeval\", \"b\": \"langwatch\"}`. From a terminal: `anchor compare deepeval langwatch`\n- Each listing in full: https://www.anchorterminal.com/api/v1/tools/deepeval.json and https://www.anchorterminal.com/api/v1/tools/langwatch.json\n\n## Other comparisons with DeepEval or LangWatch\n\n- [Arize Phoenix vs DeepEval](https://www.anchorterminal.com/compare/arize-phoenix-vs-deepeval.md)\n- [Arize Phoenix vs LangWatch](https://www.anchorterminal.com/compare/arize-phoenix-vs-langwatch.md)\n- [Baserun vs DeepEval](https://www.anchorterminal.com/compare/baserun-vs-deepeval.md)\n- [Baserun vs LangWatch](https://www.anchorterminal.com/compare/baserun-vs-langwatch.md)\n- [Braintrust API + MCP vs DeepEval](https://www.anchorterminal.com/compare/braintrust-vs-deepeval.md)\n- [Braintrust API + MCP vs LangWatch](https://www.anchorterminal.com/compare/braintrust-vs-langwatch.md)\n- [Galileo API + MCP vs LangWatch](https://www.anchorterminal.com/compare/galileo-vs-langwatch.md)\n- [Helicone AI Gateway + MCP vs LangWatch](https://www.anchorterminal.com/compare/helicone-vs-langwatch.md)\n- [HoneyHive vs LangWatch](https://www.anchorterminal.com/compare/honeyhive-vs-langwatch.md)\n- [Laminar API + MCP vs LangWatch](https://www.anchorterminal.com/compare/laminar-vs-langwatch.md)\n- [Langfuse API + MCP vs LangWatch](https://www.anchorterminal.com/compare/langfuse-vs-langwatch.md)\n- [LangSmith API + MCP vs LangWatch](https://www.anchorterminal.com/compare/langsmith-vs-langwatch.md)\n- [LangWatch vs MLflow Tracing](https://www.anchorterminal.com/compare/langwatch-vs-mlflow-tracing.md)\n- [LangWatch vs Prefactor](https://www.anchorterminal.com/compare/langwatch-vs-prefactor.md)\n- [LangWatch vs Pydantic Logfire](https://www.anchorterminal.com/compare/langwatch-vs-pydantic-logfire.md)\n- [LangWatch vs Respan API + MCP](https://www.anchorterminal.com/compare/langwatch-vs-respan.md)\n- [LangWatch vs W\u0026B Weave](https://www.anchorterminal.com/compare/langwatch-vs-wandb-weave.md)\n- [DeepEval vs Galileo API + MCP](https://www.anchorterminal.com/compare/deepeval-vs-galileo.md)\n- [DeepEval vs Helicone AI Gateway + MCP](https://www.anchorterminal.com/compare/deepeval-vs-helicone.md)\n- [DeepEval vs HoneyHive](https://www.anchorterminal.com/compare/deepeval-vs-honeyhive.md)\n- [DeepEval vs Laminar API + MCP](https://www.anchorterminal.com/compare/deepeval-vs-laminar.md)\n- [DeepEval vs Langfuse API + MCP](https://www.anchorterminal.com/compare/deepeval-vs-langfuse.md)\n- [DeepEval vs LangSmith API + MCP](https://www.anchorterminal.com/compare/deepeval-vs-langsmith.md)\n- [DeepEval vs MLflow Tracing](https://www.anchorterminal.com/compare/deepeval-vs-mlflow-tracing.md)\n- [DeepEval vs Prefactor](https://www.anchorterminal.com/compare/deepeval-vs-prefactor.md)\n- [DeepEval vs Pydantic Logfire](https://www.anchorterminal.com/compare/deepeval-vs-pydantic-logfire.md)\n- [DeepEval vs Respan API + MCP](https://www.anchorterminal.com/compare/deepeval-vs-respan.md)\n- [DeepEval vs W\u0026B Weave](https://www.anchorterminal.com/compare/deepeval-vs-wandb-weave.md)\n",
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