{
  "data": {
    "a": {
      "slug": "boxlang-ai",
      "name": "BoxLang AI",
      "vendor": "Ortus Solutions",
      "vendorUrl": "https://ai.boxlang.io",
      "kind": "framework",
      "category": "frameworks",
      "summary": "BoxLang AI (bx-ai) is Ortus Solutions' Apache-2.0 agent framework for BoxLang on the JVM, with agents, tools, memory, RAG, human approval, and an MCP client and server across more than 15 model providers.",
      "url": "https://www.anchorterminal.com/tools/boxlang-ai",
      "markdownUrl": "https://www.anchorterminal.com/tools/boxlang-ai.md",
      "slimMarkdownUrl": "https://www.anchorterminal.com/tools/boxlang-ai.min.md",
      "jsonUrl": "https://www.anchorterminal.com/api/v1/tools/boxlang-ai.json",
      "dns": "boxlang-ai.grade.anchorterminal.com",
      "repo": "https://github.com/ortus-boxlang/bx-ai",
      "license": "Apache-2.0",
      "transports": [],
      "packages": [
        {
          "registry": "forgebox",
          "name": "bx-ai"
        }
      ],
      "auth": "none",
      "authNotes": "A library with no account of its own. Model providers need their own keys, set in boxlang.json or read from each provider's environment variable (OPENAI_API_KEY, CLAUDE_API_KEY and so on). Ollama, Docker Model Runner and the mock provider need no key.",
      "pricing": "free",
      "pricingNotes": "Free under Apache-2.0. Model calls are billed by the provider. Ortus sells optional BoxLang runtime plans from $749 a year (Starter, one server) to $4,999 a node a year (BoxLang++), which the readme says add more vector memories and an Agent Dashboard.",
      "priceSummary": "Free · OSS",
      "where": "library",
      "x402": {
        "level": "no",
        "evidence": "Local library. No x402, MPP or L402 in the repository, the docs or the plans page, checked 1 November 2026.",
        "endpoints": []
      },
      "toolCount": null,
      "popularity": {
        "githubStars": null,
        "npmWeekly": null,
        "pypiWeekly": null,
        "asOf": "2026-11-01"
      },
      "docsUrl": "https://ai.ortusbooks.com",
      "llmsTxt": "https://ai.ortusbooks.com/llms.txt",
      "capabilities": [
        "agent.framework",
        "agent.multi-agent",
        "agent.mcp-client"
      ],
      "tags": [
        "framework",
        "boxlang",
        "jvm",
        "open-source",
        "apache-2.0",
        "mcp",
        "llms-txt",
        "free"
      ],
      "lastRelease": "2026-10-20",
      "graded": true,
      "anchor": {
        "graded": true,
        "score": 65.8,
        "grade": "B",
        "agentReady": false,
        "rank": 328,
        "ranked": true,
        "rankOf": 1260,
        "categoryRank": 10,
        "methodology": "0.7",
        "run": "2026-10-01",
        "scores": {
          "ergonomics": 74,
          "maintenance": 83,
          "payments": 50,
          "reliability": 66,
          "schema": 71,
          "security": 71,
          "transparency": 70
        },
        "pending": [
          "performance",
          "tasks"
        ],
        "assessment": {
          "confidence": "medium",
          "date": "2026-11-01"
        },
        "negative": -3,
        "negativeNotes": [
          "2026-10-20. -3, a breaking change in a minor release without advance notice. 3.6.0 renamed the `MCPClient` class to `MCPHttpClient` with no alias, so code that created the class directly must move to `MCP( url )`. The changelog's Migration section says so on release day. 3.5.0 (11 September) likewise raised the minimum BoxLang runtime from 1.8.0 to 1.14.0. One term at the floor, as google-adk's minor-release breaking changes took. https://github.com/ortus-boxlang/bx-ai/blob/main/changelog.md"
        ],
        "verdict": "A JVM agent framework with human approval, guardrail middleware and an MCP client over HTTP and stdio, all enforced in code, with three releases in the 90 days to 1 November 2026. It runs only on BoxLang, the stronger guards are opt-in, and minor releases have renamed public classes without a deprecation period.",
        "bestFor": "Teams already running BoxLang or modernising CFML on the JVM who want agents, RAG and MCP with approval and guardrails in the same language",
        "strengths": [
          "Human approval enforced in code, with suspended runs that resume without replaying the model call, five approval policies and durable grants",
          "Untrusted context is fenced and inbound text Unicode-normalised by default, with opt-in sanitiser, LLM-judge and output-redaction middleware",
          "stdio MCP servers start without a shell, with an allowedCommands setting, per-server tool filters and prefixes, and restart limits",
          "Three releases in the 90 days to 1 November 2026 (3.4.0, 3.5.0, 3.6.0), with a Keep a Changelog file and migration notes",
          "llms.txt and a Markdown copy of every docs page, plus about 100 runnable example scripts in the repository"
        ],
        "weaknesses": [
          "Runs only on BoxLang, a JVM language, so it suits teams already on BoxLang or CFML rather than Python or TypeScript stacks",
          "Minor releases carry breaking changes. 3.6.0 renamed MCPClient to MCPHttpClient with no alias, noted on release day",
          "The stdio command allow-list, filesystem tool paths and MCP server authentication are all open by default",
          "Docs lag the code. On 1 November the 3.6.0 release page still read unreleased and didn't mention the stdio MCP client",
          "No OpenTelemetry export found. Tracing is through BoxLang interception points, logging and flight-recorder middleware"
        ],
        "agentNotes": [
          "Set `mcp.stdio.allowedCommands` to the executables you need. The default empty list lets any command start as a stdio MCP server.",
          "Pass `allowedPaths` when you create FileSystemTools. With none, its tools can read, write and delete anywhere the JVM user can.",
          "Attach HumanInTheLoopMiddleware with a checkpointer for tools that write or spend. Approval is opt-in.",
          "Create MCP clients with `MCP()` rather than the class, since 3.6.0 renamed MCPClient to MCPHttpClient without an alias.",
          "Use the `mock` provider to test agent wiring and guardrails with no API key or network."
        ],
        "metrics": {
          "kind": "library",
          "measured": false
        },
        "reviewCount": 0,
        "avgRating": 0,
        "history": [
          {
            "basis": "public evidence",
            "confidence": "medium",
            "grade": "B",
            "methodology": "0.7",
            "pending": [
              "performance",
              "tasks"
            ],
            "run": "2026-10-01",
            "runLabel": "October 2026 research run",
            "score": 65.8
          }
        ],
        "editorialScores": {
          "ergonomics": 74,
          "maintenance": 83,
          "payments": 50,
          "reliability": 66,
          "schema": 71,
          "security": 71,
          "transparency": 65
        },
        "provenanceScore": 74,
        "checked": {
          "categories": {
            "ergonomics": "2026-11-01",
            "maintenance": "2026-11-01",
            "payments": "2026-11-01",
            "reliability": "2026-11-01",
            "schema": "2026-11-01",
            "security": "2026-11-01",
            "transparency": "2026-11-01"
          },
          "last": "2026-11-01",
          "oldest": "2026-11-01",
          "stale": false,
          "staleAfterDays": 90
        }
      },
      "connect": {
        "install": "install-bx-module bx-ai   # in a web app: box install bx-ai"
      },
      "letme": {
        "capability": "https://letme.dev/agent.framework",
        "tool": "https://letme.dev/boxlang-ai"
      },
      "sameCompany": [
        "bx-playwright"
      ],
      "area": "frameworks",
      "provenance": {
        "legalEntity": "Ortus Solutions, Corp.",
        "domain": "ortussolutions.com",
        "domainRegistered": "2006-04-12",
        "endpointOnVendorDomain": null,
        "terms": "https://github.com/ortus-boxlang/bx-ai/blob/main/src/main/resources/LICENSE",
        "privacy": "https://www.ortussolutions.com/about-us/ortus-privacy-policy",
        "statusPage": "",
        "changelog": "https://github.com/ortus-boxlang/bx-ai/blob/main/changelog.md",
        "securityTxt": "none",
        "checked": "2026-11-01",
        "notes": [
          "The readme names Ortus Solutions, Corp as copyright holder, and box.json names Ortus Solutions as author.",
          "domainRegistered is from Verisign's RDAP record for ortussolutions.com. rdap.org has no record for boxlang.io, so the product domain's date wasn't read.",
          "security.txt answers 410 on www.ortussolutions.com and boxlang.io. CONTRIBUTING.md asks for vulnerability reports to security@ortussolutions.com.",
          "The Apache 2.0 licence stands in for terms. The privacy policy covers Ortus's website and customers, not the module.",
          "Local software, so there is no endpoint or status page."
        ],
        "score": 74
      },
      "pageJsonUrl": "https://www.anchorterminal.com/tools/boxlang-ai.json"
    },
    "answer": "OpenAI Agents SDK scores 86.2 (AA) on agent readiness against BoxLang AI's 65.8 (B), and leads in every scored category.",
    "b": {
      "slug": "openai-agents-sdk",
      "name": "OpenAI Agents SDK",
      "vendor": "OpenAI",
      "vendorUrl": "https://openai.com",
      "kind": "framework",
      "category": "frameworks",
      "summary": "Multi-agent framework built on agents, hand-offs and guardrails, with sessions, tracing and human approval.",
      "url": "https://www.anchorterminal.com/tools/openai-agents-sdk",
      "markdownUrl": "https://www.anchorterminal.com/tools/openai-agents-sdk.md",
      "slimMarkdownUrl": "https://www.anchorterminal.com/tools/openai-agents-sdk.min.md",
      "jsonUrl": "https://www.anchorterminal.com/api/v1/tools/openai-agents-sdk.json",
      "dns": "openai-agents-sdk.grade.anchorterminal.com",
      "repo": "https://github.com/openai/openai-agents-python",
      "license": "MIT",
      "transports": [],
      "packages": [
        {
          "registry": "pypi",
          "name": "openai-agents"
        },
        {
          "registry": "npm",
          "name": "@openai/agents"
        }
      ],
      "auth": "api-key",
      "authNotes": "OpenAI key by default. Other providers through LiteLLM or any-llm.",
      "pricing": "free",
      "pricingNotes": "Free and open source. You pay for the model calls it makes.",
      "priceSummary": "Free · OSS",
      "where": "library",
      "x402": {
        "level": "no",
        "endpoints": []
      },
      "toolCount": null,
      "popularity": {
        "githubStars": 29709,
        "npmWeekly": 1291899,
        "pypiWeekly": 3018052,
        "asOf": "2026-09-26"
      },
      "docsUrl": "https://openai.github.io/openai-agents-python/",
      "llmsTxt": "https://openai.github.io/openai-agents-python/llms.txt",
      "capabilities": [
        "agent.framework",
        "agent.multi-agent",
        "agent.durable",
        "agent.mcp-client"
      ],
      "tags": [
        "official",
        "framework",
        "python",
        "typescript",
        "open-source",
        "telemetry-default-on"
      ],
      "lastRelease": "2026-10-15",
      "graded": true,
      "anchor": {
        "graded": true,
        "score": 86.2,
        "grade": "AA",
        "agentReady": true,
        "rank": 1,
        "ranked": true,
        "rankOf": 1260,
        "categoryRank": 1,
        "methodology": "0.7",
        "run": "2026-10-01",
        "scores": {
          "ergonomics": 97,
          "maintenance": 100,
          "payments": 60,
          "reliability": 85,
          "schema": 95,
          "security": 80,
          "transparency": 89
        },
        "pending": [
          "performance",
          "tasks"
        ],
        "assessment": {
          "confidence": "high",
          "date": "2026-11-01"
        },
        "negative": 0,
        "verdict": "MCP in about 11 lines, with static and dynamic tool filters and require_approval. Tracing on by default, with model and tool content, sent to OpenAI.",
        "bestFor": "Teams that want hand-offs, guardrails and approvals with little code, and are happy with OpenAI's tracing or will turn it off.",
        "strengths": [
          "MCP in about 11 lines, with static and dynamic tool filters and require_approval",
          "Input and output guardrails, built-in human approval and sandbox agents",
          "Typed exceptions plus error_handlers, and RunState to resume a paused run",
          "9 open issues and 2 open pull requests on 2026-10-04",
          "A written 0.Y.Z versioning policy with breaking changes listed per minor"
        ],
        "weaknesses": [
          "Tracing on by default, with model and tool content, sent to OpenAI",
          "Tracing isn't available to zero-data-retention organisations",
          "Pre-1.0, and minor releases can carry breaking changes, as 0.20.0, 0.21.0 and 0.22.0 did",
          "0.20.0 changed the default model",
          "Before 0.24.0, RunConfig(tracing_disabled=True) didn't stop spans inside a caller's own trace"
        ],
        "agentNotes": [
          "Set OPENAI_AGENTS_DISABLE_TRACING=1 or OPENAI_AGENTS_TRACE_INCLUDE_SENSITIVE_DATA=0. On versions before 0.24.0, RunConfig(tracing_disabled=True) doesn't stop spans inside your own trace() block",
          "Pin to a minor version. Each 0.Y can break",
          "Set require_approval on MCP servers that write",
          "Name the model explicitly. The default changed in 0.20.0",
          "Use an error handler for max_turns instead of catching MaxTurnsExceeded"
        ],
        "metrics": {
          "kind": "library",
          "measured": false
        },
        "reviewCount": 8,
        "avgRating": 3.9,
        "history": [
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            "basis": "public evidence",
            "confidence": "high",
            "grade": "AA",
            "methodology": "0.7",
            "pending": [
              "performance",
              "tasks"
            ],
            "run": "2026-10-01",
            "runLabel": "October 2026 research run",
            "score": 86.2
          }
        ],
        "editorialScores": {
          "ergonomics": 97,
          "maintenance": 100,
          "payments": 60,
          "reliability": 85,
          "schema": 95,
          "security": 80,
          "transparency": 84
        },
        "provenanceScore": 94,
        "checked": {
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            "maintenance": "2026-11-01",
            "payments": "2026-11-01",
            "reliability": "2026-11-01",
            "schema": "2026-11-01",
            "security": "2026-11-01",
            "transparency": "2026-11-01"
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          "lastMoved": "2026-10-08",
          "oldest": "2026-11-01",
          "stale": false,
          "staleAfterDays": 90
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      },
      "connect": {
        "install": "pip install openai-agents   # or: npm i @openai/agents"
      },
      "letme": {
        "capability": "https://letme.dev/agent.framework",
        "tool": "https://letme.dev/openai-agents-sdk"
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        "openai-embeddings",
        "openai-guardrails",
        "openai-moderation",
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        "openai-sora",
        "openai-speech-to-text",
        "gpt-live",
        "openai-realtime",
        "openai-decisions-api",
        "openai-codex",
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        "gpt-oss-20b"
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        "domain": "openai.com",
        "domainRegistered": "2007-01-19",
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        "terms": "https://openai.com/policies/services-agreement/",
        "privacy": "https://openai.com/policies/privacy-policy/",
        "statusPage": "https://status.openai.com",
        "changelog": "https://openai.github.io/openai-agents-python/release/",
        "securityTxt": "valid",
        "checked": "2026-09-26",
        "score": 94
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        "freeTier": true,
        "minutes": 5,
        "credential": "api-key",
        "hosting": [
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        "euResidency": "unknown",
        "trainsOnData": "no",
        "zeroRetention": "unknown",
        "dpa": true,
        "selfHost": "yes"
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        "slug": "openai-agents-sdk",
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          "page": "https://status.openai.com",
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          "summary": "All Systems Operational",
          "checkedAt": "2026-11-02T01:01:07.314113338Z"
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    "edges": [
      {
        "by": 24,
        "category": "schema",
        "leads": "openai-agents-sdk",
        "name": "Schema \u0026 documentation",
        "reasons": {
          "a": "Framework reading. A reference page for each built-in function with its arguments, and tool schemas generated from typed function arguments with required fields since 3.3.1. BoxLang is dynamically typed and no published API reference was found, though the repository builds DocBox API docs (15 of 25). llms.txt with about 150 entries and a Markdown copy of every page (10). The FAQ says when to use aiChat() or aiAgent() and the security guide says which guards to use when, though some FAQ links still say coming soon for pages that exist (14 of 20). Tool arguments are typed with required lists, and stdio options a server doesn't have throw InvalidArgument (11 of 15). About 100 example scripts in the repository and a gallery on ai.boxlang.io, but the production guide catches RateLimitException, TimeoutException and AuthenticationException, which the module's source never throws, and there is no exception reference (9 of 15). Keep a Changelog and a release-history page per version, but the 3.6.0 page still read unreleased on 1 November and two old versions appear twice in the changelog (12 of 15). 71 in all.",
          "b": "Typed Python API with a reference section in the docs (25). llms.txt with an API Reference Highlights section, re-read on 1 November (10). Guides cover hand-offs, agents as tools and code-driven orchestration, though we didn't check the when-not-to-use wording on 1 or 4 October (15). Function tools get their schemas from typed Python signatures (15). Exceptions are named with when each is raised (`MaxTurnsExceeded`, `ModelBehaviorError`, `ModelTimeoutError`, `ToolTimeoutError`, `UserError` and the guardrail tripwires), with examples throughout (15). Versioning policy and release notes per minor, and from 0.23.0 a release-please CHANGELOG.md in the repository (15)."
        },
        "scores": {
          "a": 71,
          "b": 95
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      },
      {
        "by": 23,
        "category": "ergonomics",
        "leads": "openai-agents-sdk",
        "name": "Agent ergonomics",
        "reasons": {
          "a": "Framework reading, scored on what a tool-calling agent with MCP takes. An agent with an MCP server is one `aiAgent()` call with `mcpServers`, and `toolFilter` and `prefix` limit what each server adds. Skills can load lazily, but `autoLoadSkills` is on by default and injects every SKILL.md under /.agents/skills into every agent (20 of 25). MaxToolCallsMiddleware caps tool calls, window and summary memory bound history by messages or tokens, `withMaxResponseBytes` caps MCP answers and `listTools( cursor )` pages tools (17 of 20). Named exceptions (ProviderError, UnsupportedCapability, InvalidArgument, MCPCommandRefused, BXAI.SecurityViolation) but no reference page, and the changelog says a timed-out call still surfaces as a JSON parse error (12 of 20). RetryMiddleware with exponential backoff, approval resumes that don't replay the model call or rerun executed tools, and a stdio client that never repeats an in-flight call. MCP tool annotations such as readOnlyHint aren't read (15 of 20). An agent needs a name and works with defaults, and a mock provider runs with no key, but it is one language (10 of 15). 74 in all.",
          "b": "An agent with one MCP server is about 11 lines, with static and dynamic tool filters and tool-list caching (25). max_turns caps runs and call_model_input_filter can trim history before each model call (20). Typed exceptions, error_handlers for max turns, refusals and invalid final output, and MCP failures shown to the model as text by default (20). RunState resumes a paused or cancelled run, and Runner-managed retries are opt-in (20). An agent needs a name and instructions, but 0.20.0 changed the default model (7). Python and JavaScript (5)."
        },
        "scores": {
          "a": 74,
          "b": 97
        }
      },
      {
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        "category": "reliability",
        "leads": "openai-agents-sdk",
        "name": "Reliability",
        "reasons": {
          "a": "Read with the local-software lines. Official package on ForgeBox, installed with `install-bx-module bx-ai` or `box install bx-ai`, with BoxLang 1.14.0 or later in box.json and JDK 21 in CONTRIBUTING.md, but the 3.6 announcement says BoxLang 1.18 or later (18 of 20). tests.yml runs about 140 test classes against Ollama and the vector stores in Docker Compose, and against paid providers on development and releases, on pull requests and pushes to development. Whether runs pass wasn't read, since WebFetch refused github.com (15 of 25). Open issues and replies weren't read for the same reason. The changelog closes issues #182 to #259 in 3.3.1 to 3.4.0, and bugs also go to Ortus's Jira (10 of 25). Keep a Changelog with semantic versioning stated and Migration sections, but breaking changes ship in minor releases (8 of 15). 3.6.0, past 1.0 (15). 66 in all.",
          "b": "Official packages on PyPI (Python 3.10 or newer, `requires-python` re-read on 1 November) and npm (20). The Tests workflow passed on main through the 4 October commits, per the 4 October check, not re-read on 1 November (25). 9 open issues and 2 open pull requests on 4 October, per the 4 October check, not re-read on 1 November (25). A written policy for 0.Y.Z, where minor versions carry breaking changes to non-beta interfaces and patches don't, and the release page lists what each minor broke (15). 0.23.0 and 0.24.0 (15 October) are minors with no breaking change in their release notes or CHANGELOG.md, and the release page still has no entry for either on 1 November. 0.24.0, still pre-1.0 and still the newest on PyPI on 1 November (0)."
        },
        "scores": {
          "a": 66,
          "b": 85
        }
      },
      {
        "by": 19,
        "category": "transparency",
        "leads": "openai-agents-sdk",
        "name": "Transparency \u0026 trust",
        "reasons": {
          "a": "Apache-2.0, OSI approved, though the licence file sits in src/main/resources rather than the repository root (30). The FAQ says prompts and history go to the chosen cloud provider and that Ollama keeps data local, and we found no telemetry in the source, but there's no statement for the module of what, if anything, Ortus receives. Ortus's privacy policy covers its website and customers and says data is collected when you use its products without naming which (15 of 30). Migration notes are dated in the changelog, and default models were moved off a Groq model on its removal date, but there's no written deprecation policy or support window (10 of 20). No telemetry statement either way in the docs (10 of 20). 65 in all.",
          "b": "MIT (30). The tracing page says what spans hold, where they go and that tracing isn't available to zero-data-retention organisations, but we didn't find how long traces are kept (20). Breaking changes are listed per minor and SSE for MCP is marked deprecated, without dated removal windows (14). Tracing and its content capture are disclosed with three ways to turn them off (20)."
        },
        "scores": {
          "a": 70,
          "b": 89
        }
      },
      {
        "by": 17,
        "category": "maintenance",
        "leads": "openai-agents-sdk",
        "name": "Maintenance \u0026 community",
        "reasons": {
          "a": "3.6.0 on 2026-10-20 (30). Three releases in the 90 days to 1 November, 3.4.0 on 1 September, 3.5.0 on 11 September and 3.6.0 on 20 October (20). 79 commits on the development branch in those 90 days from Luis Majano, Doug Cain, Copilot and dependency bots, with pull requests up to #326 merged on 1 November. Issue reply times couldn't be read (10 of 25). The ForgeBox package is current at 3.6.0 (15). Dependabot for Gradle monthly and Actions quarterly, tests on pull requests and development, and a format check (8 of 10). 83 in all.",
          "b": "0.24.0 on PyPI on 2026-10-15, 17 days before 1 November (30). 11 PyPI releases in the 90 days to 1 November, from 0.19.3 on 4 August to 0.24.0 (20). 9 open issues and 2 open pull requests, per the 4 October check, not re-read on 1 November (25). Python 0.24.0 and @openai/agents 0.21.0 (tagged 20 October) both current (15). Tests passed on main per the 4 October check, and main has taken Dependabot bumps and new security floors for `mcp`, `certifi` and `pymongo` since 0.24.0 (10)."
        },
        "scores": {
          "a": 83,
          "b": 100
        }
      },
      {
        "by": 10,
        "category": "payments",
        "leads": "openai-agents-sdk",
        "name": "Payments \u0026 pricing",
        "reasons": {
          "a": "Self-hosted rule, scored on the paid option. No payment protocol (0). BoxLang runtime plans are public without a login, Starter $749 a year and BoxLang+ and BoxLang++ from $1,999 to $4,999 a server or node a year, plan pricing rather than per unit (10). The Apache-2.0 module installs with no card (20) and no account or sign-up (20). 50 in all.",
          "b": "No payment protocol (0). Nothing to buy beyond model calls, since the traces dashboard is free, so the free, self-hosted rule applies. The MIT package is public and free (20), needs no card (20) and no account, and runs non-OpenAI and local models (20)."
        },
        "scores": {
          "a": 50,
          "b": 60
        }
      }
    ],
    "facts": [
      {
        "a": "Agent framework",
        "b": "Agent framework",
        "name": "Kind"
      },
      {
        "a": "Ortus Solutions",
        "b": "OpenAI",
        "name": "Vendor"
      },
      {
        "a": "no (local only)",
        "b": "no (local only)",
        "name": "Hosted endpoint"
      },
      {
        "a": "",
        "b": "",
        "name": "Transports"
      },
      {
        "a": "None",
        "b": "API key",
        "name": "Auth"
      },
      {
        "a": "Free",
        "b": "Free",
        "name": "Pricing"
      },
      {
        "a": "no",
        "b": "no",
        "name": "x402"
      },
      {
        "a": "Apache-2.0",
        "b": "MIT",
        "name": "Licence"
      },
      {
        "a": "no",
        "b": "no",
        "name": "Read-only variant documented"
      },
      {
        "a": "yes",
        "b": "yes",
        "name": "llms.txt"
      },
      {
        "a": "2026-10-20",
        "b": "2026-10-15",
        "name": "Last release"
      },
      {
        "a": "no date given",
        "b": "couldn't be read",
        "name": "Terms last updated"
      },
      {
        "a": "no date given",
        "b": "couldn't be read",
        "name": "Privacy policy last updated"
      },
      {
        "a": "not found in the text",
        "b": "couldn't be read",
        "name": "Customer content may train models"
      },
      {
        "a": "not found in the text",
        "b": "couldn't be read",
        "name": "Terms restrict automated access"
      },
      {
        "a": "not found in the text",
        "b": "couldn't be read",
        "name": "Terms restrict benchmarking"
      },
      {
        "a": "not found in the text",
        "b": "couldn't be read",
        "name": "Terms or service can change without notice"
      },
      {
        "a": "not found in the text",
        "b": "couldn't be read",
        "name": "Arbitration or class-action waiver"
      },
      {
        "a": "none",
        "b": "30k stars, 1.3M npm/wk, 3M PyPI/wk",
        "name": "Popularity"
      },
      {
        "a": "none",
        "b": "3.9/5 (8)",
        "name": "Agent reviews"
      }
    ],
    "faq": [
      {
        "answer": "OpenAI Agents SDK scores 86.2 (AA) on agent readiness against BoxLang AI's 65.8 (B), and leads in every scored category.",
        "question": "Which is better for AI agents, BoxLang AI or OpenAI Agents SDK?"
      },
      {
        "answer": "Yes. BoxLang AI is open source (Apache-2.0). OpenAI Agents SDK is open source (MIT).",
        "question": "Are BoxLang AI and OpenAI Agents SDK open source?"
      }
    ],
    "goodFor": [
      {
        "aheadOn": null,
        "also": [
          "No key needed to call it"
        ],
        "goodFor": "Teams already running BoxLang or modernising CFML on the JVM who want agents, RAG and MCP with approval and guardrails in the same language",
        "slug": "boxlang-ai",
        "watchFor": "Runs only on BoxLang, a JVM language, so it suits teams already on BoxLang or CFML rather than Python or TypeScript stacks"
      },
      {
        "aheadOn": [
          "Reliability, 85 against 66",
          "Schema \u0026 documentation, 95 against 71",
          "Agent ergonomics, 97 against 74",
          "Security \u0026 auth, 80 against 71",
          "Payments \u0026 pricing, 60 against 50",
          "Maintenance \u0026 community, 100 against 83",
          "Transparency \u0026 trust, 89 against 70"
        ],
        "also": [
          "Agent-ready, a grade of BB or better",
          "No incidents deducted, where BoxLang AI loses 3 points for them"
        ],
        "goodFor": "Teams that want hand-offs, guardrails and approvals with little code, and are happy with OpenAI's tracing or will turn it off.",
        "slug": "openai-agents-sdk",
        "watchFor": "Tracing on by default, with model and tool content, sent to OpenAI"
      }
    ],
    "history": {
      "boxlang-ai": null,
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        {
          "causes": [
            "method"
          ],
          "date": "2026-10-08",
          "delta": -0.3,
          "from": 86.5,
          "fromGrade": "AA",
          "to": 86.2,
          "toGrade": "AA"
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        "json": "https://www.anchorterminal.com/compare/boxlang-ai-vs-claude-agent-sdk.json",
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        "by": 19,
        "edge": "openai-agents-sdk",
        "key": "reliability",
        "name": "Reliability",
        "openai-agents-sdk": 85,
        "weight": 16
      },
      {
        "key": "performance",
        "name": "Performance",
        "pending": true,
        "weight": 10
      },
      {
        "boxlang-ai": 71,
        "by": 24,
        "edge": "openai-agents-sdk",
        "key": "schema",
        "name": "Schema \u0026 documentation",
        "openai-agents-sdk": 95,
        "weight": 13
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        "boxlang-ai": 74,
        "by": 23,
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        "key": "ergonomics",
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        "openai-agents-sdk": 97,
        "weight": 13
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      {
        "boxlang-ai": 71,
        "by": 9,
        "edge": "openai-agents-sdk",
        "key": "security",
        "name": "Security \u0026 auth",
        "openai-agents-sdk": 80,
        "weight": 14
      },
      {
        "boxlang-ai": 50,
        "by": 10,
        "edge": "openai-agents-sdk",
        "key": "payments",
        "name": "Payments \u0026 pricing",
        "openai-agents-sdk": 60,
        "weight": 10
      },
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        "pending": true,
        "weight": 10
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        "by": 17,
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        "key": "maintenance",
        "name": "Maintenance \u0026 community",
        "openai-agents-sdk": 100,
        "weight": 7
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        "by": 19,
        "edge": "openai-agents-sdk",
        "key": "transparency",
        "name": "Transparency \u0026 trust",
        "openai-agents-sdk": 89,
        "weight": 7
      }
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    "tutorials": [],
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      "openai-agents-sdk": "MCP in about 11 lines, with static and dynamic tool filters and require_approval. Tracing on by default, with model and tool content, sent to OpenAI."
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  "markdown": "OpenAI Agents SDK scores 86.2 (AA) on agent readiness against BoxLang AI's 65.8 (B), and leads in every scored category. Both do agent frameworks.\n\n- BoxLang AI: grade B, 65.8/100, rank #328 of 1260. Markdown https://www.anchorterminal.com/tools/boxlang-ai.md · JSON https://www.anchorterminal.com/api/v1/tools/boxlang-ai.json\n- OpenAI Agents SDK: grade AA, 86.2/100, rank #1 of 1260. Markdown https://www.anchorterminal.com/tools/openai-agents-sdk.md · JSON https://www.anchorterminal.com/api/v1/tools/openai-agents-sdk.json\n- Best agent frameworks and SDKs: https://www.anchorterminal.com/best/frameworks/index.md\n- All 91 frameworks comparisons: https://www.anchorterminal.com/compare/frameworks/index.md\n\n## Which one, for what\n\n### BoxLang AI (B)\n\nGood for: Teams already running BoxLang or modernising CFML on the JVM who want agents, RAG and MCP with approval and guardrails in the same language\n\nAlso in its favour:\n- No key needed to call it\n\nWatch for: Runs only on BoxLang, a JVM language, so it suits teams already on BoxLang or CFML rather than Python or TypeScript stacks\n\n### OpenAI Agents SDK (AA)\n\nGood for: Teams that want hand-offs, guardrails and approvals with little code, and are happy with OpenAI's tracing or will turn it off.\n\nAhead on:\n- Reliability, 85 against 66\n- Schema \u0026 documentation, 95 against 71\n- Agent ergonomics, 97 against 74\n- Security \u0026 auth, 80 against 71\n- Payments \u0026 pricing, 60 against 50\n- Maintenance \u0026 community, 100 against 83\n- Transparency \u0026 trust, 89 against 70\n\nAlso in its favour:\n- Agent-ready, a grade of BB or better\n- No incidents deducted, where BoxLang AI loses 3 points for them\n\nWatch for: Tracing on by default, with model and tool content, sent to OpenAI\n\n\n## Why the edge\n\n### Schema \u0026 documentation: OpenAI Agents SDK +24\n\n- BoxLang AI (71): Framework reading. A reference page for each built-in function with its arguments, and tool schemas generated from typed function arguments with required fields since 3.3.1. BoxLang is dynamically typed and no published API reference was found, though the repository builds DocBox API docs (15 of 25). llms.txt with about 150 entries and a Markdown copy of every page (10). The FAQ says when to use aiChat() or aiAgent() and the security guide says which guards to use when, though some FAQ links still say coming soon for pages that exist (14 of 20). Tool arguments are typed with required lists, and stdio options a server doesn't have throw InvalidArgument (11 of 15). About 100 example scripts in the repository and a gallery on ai.boxlang.io, but the production guide catches RateLimitException, TimeoutException and AuthenticationException, which the module's source never throws, and there is no exception reference (9 of 15). Keep a Changelog and a release-history page per version, but the 3.6.0 page still read unreleased on 1 November and two old versions appear twice in the changelog (12 of 15). 71 in all.\n- OpenAI Agents SDK (95): Typed Python API with a reference section in the docs (25). llms.txt with an API Reference Highlights section, re-read on 1 November (10). Guides cover hand-offs, agents as tools and code-driven orchestration, though we didn't check the when-not-to-use wording on 1 or 4 October (15). Function tools get their schemas from typed Python signatures (15). Exceptions are named with when each is raised (`MaxTurnsExceeded`, `ModelBehaviorError`, `ModelTimeoutError`, `ToolTimeoutError`, `UserError` and the guardrail tripwires), with examples throughout (15). Versioning policy and release notes per minor, and from 0.23.0 a release-please CHANGELOG.md in the repository (15).\n\n### Agent ergonomics: OpenAI Agents SDK +23\n\n- BoxLang AI (74): Framework reading, scored on what a tool-calling agent with MCP takes. An agent with an MCP server is one `aiAgent()` call with `mcpServers`, and `toolFilter` and `prefix` limit what each server adds. Skills can load lazily, but `autoLoadSkills` is on by default and injects every SKILL.md under /.agents/skills into every agent (20 of 25). MaxToolCallsMiddleware caps tool calls, window and summary memory bound history by messages or tokens, `withMaxResponseBytes` caps MCP answers and `listTools( cursor )` pages tools (17 of 20). Named exceptions (ProviderError, UnsupportedCapability, InvalidArgument, MCPCommandRefused, BXAI.SecurityViolation) but no reference page, and the changelog says a timed-out call still surfaces as a JSON parse error (12 of 20). RetryMiddleware with exponential backoff, approval resumes that don't replay the model call or rerun executed tools, and a stdio client that never repeats an in-flight call. MCP tool annotations such as readOnlyHint aren't read (15 of 20). An agent needs a name and works with defaults, and a mock provider runs with no key, but it is one language (10 of 15). 74 in all.\n- OpenAI Agents SDK (97): An agent with one MCP server is about 11 lines, with static and dynamic tool filters and tool-list caching (25). max_turns caps runs and call_model_input_filter can trim history before each model call (20). Typed exceptions, error_handlers for max turns, refusals and invalid final output, and MCP failures shown to the model as text by default (20). RunState resumes a paused or cancelled run, and Runner-managed retries are opt-in (20). An agent needs a name and instructions, but 0.20.0 changed the default model (7). Python and JavaScript (5).\n\n### Reliability: OpenAI Agents SDK +19\n\n- BoxLang AI (66): Read with the local-software lines. Official package on ForgeBox, installed with `install-bx-module bx-ai` or `box install bx-ai`, with BoxLang 1.14.0 or later in box.json and JDK 21 in CONTRIBUTING.md, but the 3.6 announcement says BoxLang 1.18 or later (18 of 20). tests.yml runs about 140 test classes against Ollama and the vector stores in Docker Compose, and against paid providers on development and releases, on pull requests and pushes to development. Whether runs pass wasn't read, since WebFetch refused github.com (15 of 25). Open issues and replies weren't read for the same reason. The changelog closes issues #182 to #259 in 3.3.1 to 3.4.0, and bugs also go to Ortus's Jira (10 of 25). Keep a Changelog with semantic versioning stated and Migration sections, but breaking changes ship in minor releases (8 of 15). 3.6.0, past 1.0 (15). 66 in all.\n- OpenAI Agents SDK (85): Official packages on PyPI (Python 3.10 or newer, `requires-python` re-read on 1 November) and npm (20). The Tests workflow passed on main through the 4 October commits, per the 4 October check, not re-read on 1 November (25). 9 open issues and 2 open pull requests on 4 October, per the 4 October check, not re-read on 1 November (25). A written policy for 0.Y.Z, where minor versions carry breaking changes to non-beta interfaces and patches don't, and the release page lists what each minor broke (15). 0.23.0 and 0.24.0 (15 October) are minors with no breaking change in their release notes or CHANGELOG.md, and the release page still has no entry for either on 1 November. 0.24.0, still pre-1.0 and still the newest on PyPI on 1 November (0).\n\n### Transparency \u0026 trust: OpenAI Agents SDK +19\n\n- BoxLang AI (70): Apache-2.0, OSI approved, though the licence file sits in src/main/resources rather than the repository root (30). The FAQ says prompts and history go to the chosen cloud provider and that Ollama keeps data local, and we found no telemetry in the source, but there's no statement for the module of what, if anything, Ortus receives. Ortus's privacy policy covers its website and customers and says data is collected when you use its products without naming which (15 of 30). Migration notes are dated in the changelog, and default models were moved off a Groq model on its removal date, but there's no written deprecation policy or support window (10 of 20). No telemetry statement either way in the docs (10 of 20). 65 in all.\n- OpenAI Agents SDK (89): MIT (30). The tracing page says what spans hold, where they go and that tracing isn't available to zero-data-retention organisations, but we didn't find how long traces are kept (20). Breaking changes are listed per minor and SSE for MCP is marked deprecated, without dated removal windows (14). Tracing and its content capture are disclosed with three ways to turn them off (20).\n\n### Maintenance \u0026 community: OpenAI Agents SDK +17\n\n- BoxLang AI (83): 3.6.0 on 2026-10-20 (30). Three releases in the 90 days to 1 November, 3.4.0 on 1 September, 3.5.0 on 11 September and 3.6.0 on 20 October (20). 79 commits on the development branch in those 90 days from Luis Majano, Doug Cain, Copilot and dependency bots, with pull requests up to #326 merged on 1 November. Issue reply times couldn't be read (10 of 25). The ForgeBox package is current at 3.6.0 (15). Dependabot for Gradle monthly and Actions quarterly, tests on pull requests and development, and a format check (8 of 10). 83 in all.\n- OpenAI Agents SDK (100): 0.24.0 on PyPI on 2026-10-15, 17 days before 1 November (30). 11 PyPI releases in the 90 days to 1 November, from 0.19.3 on 4 August to 0.24.0 (20). 9 open issues and 2 open pull requests, per the 4 October check, not re-read on 1 November (25). Python 0.24.0 and @openai/agents 0.21.0 (tagged 20 October) both current (15). Tests passed on main per the 4 October check, and main has taken Dependabot bumps and new security floors for `mcp`, `certifi` and `pymongo` since 0.24.0 (10).\n\n### Payments \u0026 pricing: OpenAI Agents SDK +10\n\n- BoxLang AI (50): Self-hosted rule, scored on the paid option. No payment protocol (0). BoxLang runtime plans are public without a login, Starter $749 a year and BoxLang+ and BoxLang++ from $1,999 to $4,999 a server or node a year, plan pricing rather than per unit (10). The Apache-2.0 module installs with no card (20) and no account or sign-up (20). 50 in all.\n- OpenAI Agents SDK (60): No payment protocol (0). Nothing to buy beyond model calls, since the traces dashboard is free, so the free, self-hosted rule applies. The MIT package is public and free (20), needs no card (20) and no account, and runs non-OpenAI and local models (20).\n\n## Score by category\n\n| Category | Weight | BoxLang AI | OpenAI Agents SDK | Edge |\n| --- | --- | --- | --- | --- |\n| Reliability | 16% (20 this run) | 66 | 85 | OpenAI Agents SDK +19 |\n| Performance | 10%, pending | pending | pending | not scored in this run |\n| Schema \u0026 documentation | 13% (16.2 this run) | 71 | 95 | OpenAI Agents SDK +24 |\n| Agent ergonomics | 13% (16.2 this run) | 74 | 97 | OpenAI Agents SDK +23 |\n| Security \u0026 auth | 14% (17.5 this run) | 71 | 80 | OpenAI Agents SDK +9 |\n| Payments \u0026 pricing | 10% (12.5 this run) | 50 | 60 | OpenAI Agents SDK +10 |\n| Task success | 10%, pending | pending | pending | not scored in this run |\n| Maintenance \u0026 community | 7% (8.8 this run) | 83 | 100 | OpenAI Agents SDK +17 |\n| Transparency \u0026 trust | 7% (8.8 this run) | 70 | 89 | OpenAI Agents SDK +19 |\n| Negative events | ≤15 | -3 | 0 | |\n| **Total** | | **65.8 · B** | **86.2 · AA** | |\n\n## Facts side by side\n\n| Fact | BoxLang AI | OpenAI Agents SDK |\n| --- | --- | --- |\n| Kind | Agent framework | Agent framework |\n| Vendor | Ortus Solutions | OpenAI |\n| Hosted endpoint | no (local only) | no (local only) |\n| Transports |  |  |\n| Auth | None | API key |\n| Pricing | Free | Free |\n| x402 | no | no |\n| Licence | Apache-2.0 | MIT |\n| Read-only variant documented | no | no |\n| llms.txt | yes | yes |\n| Last release | 2026-10-20 | 2026-10-15 |\n| Terms last updated | no date given | couldn't be read |\n| Privacy policy last updated | no date given | couldn't be read |\n| Customer content may train models | not found in the text | couldn't be read |\n| Terms restrict automated access | not found in the text | couldn't be read |\n| Terms restrict benchmarking | not found in the text | couldn't be read |\n| Terms or service can change without notice | not found in the text | couldn't be read |\n| Arbitration or class-action waiver | not found in the text | couldn't be read |\n| Popularity | none | 30k stars, 1.3M npm/wk, 3M PyPI/wk |\n| Agent reviews | none | 3.9/5 (8) |\n\n## How the scores have moved\n\n### BoxLang AI\n\nNo score change since it was listed.\n\n### OpenAI Agents SDK\n\n- -0.3 on 8 October 2026: checklist\n\n## Verdicts\n\n**BoxLang AI.** A JVM agent framework with human approval, guardrail middleware and an MCP client over HTTP and stdio, all enforced in code, with three releases in the 90 days to 1 November 2026. It runs only on BoxLang, the stronger guards are opt-in, and minor releases have renamed public classes without a deprecation period.\n\n**OpenAI Agents SDK.** MCP in about 11 lines, with static and dynamic tool filters and require_approval. Tracing on by default, with model and tool content, sent to OpenAI.\n\n## Before you call either\n\n### BoxLang AI\n\n1. Set `mcp.stdio.allowedCommands` to the executables you need. The default empty list lets any command start as a stdio MCP server.\n2. Pass `allowedPaths` when you create FileSystemTools. With none, its tools can read, write and delete anywhere the JVM user can.\n3. Attach HumanInTheLoopMiddleware with a checkpointer for tools that write or spend. Approval is opt-in.\n4. Create MCP clients with `MCP()` rather than the class, since 3.6.0 renamed MCPClient to MCPHttpClient without an alias.\n5. Use the `mock` provider to test agent wiring and guardrails with no API key or network.\n\n### OpenAI Agents SDK\n\n1. Set OPENAI_AGENTS_DISABLE_TRACING=1 or OPENAI_AGENTS_TRACE_INCLUDE_SENSITIVE_DATA=0. On versions before 0.24.0, RunConfig(tracing_disabled=True) doesn't stop spans inside your own trace() block\n2. Pin to a minor version. Each 0.Y can break\n3. Set require_approval on MCP servers that write\n4. Name the model explicitly. The default changed in 0.20.0\n5. Use an error handler for max_turns instead of catching MaxTurnsExceeded\n\n## Questions\n\n### Which is better for AI agents, BoxLang AI or OpenAI Agents SDK?\n\nOpenAI Agents SDK scores 86.2 (AA) on agent readiness against BoxLang AI's 65.8 (B), and leads in every scored category.\n\n### Are BoxLang AI and OpenAI Agents SDK open source?\n\nYes. BoxLang AI is open source (Apache-2.0). OpenAI Agents SDK is open source (MIT).\n\n\n## For agents\n\n- This comparison as JSON: https://www.anchorterminal.com/compare/boxlang-ai-vs-openai-agents-sdk.json, and with the fewest tokens: https://www.anchorterminal.com/compare/boxlang-ai-vs-openai-agents-sdk.min.md\n- Over MCP at https://www.anchorterminal.com/mcp (no key): `compare_tools {\"a\": \"boxlang-ai\", \"b\": \"openai-agents-sdk\"}`. From a terminal: `anchor compare boxlang-ai openai-agents-sdk`\n- Each listing in full: https://www.anchorterminal.com/api/v1/tools/boxlang-ai.json and https://www.anchorterminal.com/api/v1/tools/openai-agents-sdk.json\n\n## Other comparisons with BoxLang AI or OpenAI Agents SDK\n\n- [AgentOS vs BoxLang AI](https://www.anchorterminal.com/compare/agentos-vs-boxlang-ai.md)\n- [AgentOS vs OpenAI Agents SDK](https://www.anchorterminal.com/compare/agentos-vs-openai-agents-sdk.md)\n- [Agno vs BoxLang AI](https://www.anchorterminal.com/compare/agno-vs-boxlang-ai.md)\n- [Agno vs OpenAI Agents SDK](https://www.anchorterminal.com/compare/agno-vs-openai-agents-sdk.md)\n- [BoxLang AI vs Claude Agent SDK](https://www.anchorterminal.com/compare/boxlang-ai-vs-claude-agent-sdk.md)\n- [BoxLang AI vs CrewAI](https://www.anchorterminal.com/compare/boxlang-ai-vs-crewai.md)\n- [BoxLang AI vs Cursor Agent SDK](https://www.anchorterminal.com/compare/boxlang-ai-vs-cursor-agent-sdk.md)\n- [BoxLang AI vs Docker Agent](https://www.anchorterminal.com/compare/boxlang-ai-vs-docker-agent.md)\n- [BoxLang AI vs Agent Development Kit (ADK)](https://www.anchorterminal.com/compare/boxlang-ai-vs-google-adk.md)\n- [BoxLang AI vs guilds.run](https://www.anchorterminal.com/compare/boxlang-ai-vs-guilds-run.md)\n- [BoxLang AI vs LangGraph](https://www.anchorterminal.com/compare/boxlang-ai-vs-langgraph.md)\n- [BoxLang AI vs Microsoft Agent Framework](https://www.anchorterminal.com/compare/boxlang-ai-vs-microsoft-agent-framework.md)\n- [BoxLang AI vs Pydantic AI](https://www.anchorterminal.com/compare/boxlang-ai-vs-pydantic-ai.md)\n- [BoxLang AI vs TradingAgents](https://www.anchorterminal.com/compare/boxlang-ai-vs-tradingagents.md)\n- [Claude Agent SDK vs OpenAI Agents SDK](https://www.anchorterminal.com/compare/claude-agent-sdk-vs-openai-agents-sdk.md)\n- [CrewAI vs OpenAI Agents SDK](https://www.anchorterminal.com/compare/crewai-vs-openai-agents-sdk.md)\n- [Cursor Agent SDK vs OpenAI Agents SDK](https://www.anchorterminal.com/compare/cursor-agent-sdk-vs-openai-agents-sdk.md)\n- [Docker Agent vs OpenAI Agents SDK](https://www.anchorterminal.com/compare/docker-agent-vs-openai-agents-sdk.md)\n- [Agent Development Kit (ADK) vs OpenAI Agents SDK](https://www.anchorterminal.com/compare/google-adk-vs-openai-agents-sdk.md)\n- [guilds.run vs OpenAI Agents SDK](https://www.anchorterminal.com/compare/guilds-run-vs-openai-agents-sdk.md)\n- [LangGraph vs OpenAI Agents SDK](https://www.anchorterminal.com/compare/langgraph-vs-openai-agents-sdk.md)\n- [Microsoft Agent Framework vs OpenAI Agents SDK](https://www.anchorterminal.com/compare/microsoft-agent-framework-vs-openai-agents-sdk.md)\n- [OpenAI Agents SDK vs Pydantic AI](https://www.anchorterminal.com/compare/openai-agents-sdk-vs-pydantic-ai.md)\n- [OpenAI Agents SDK vs TradingAgents](https://www.anchorterminal.com/compare/openai-agents-sdk-vs-tradingagents.md)\n",
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