{ "data": { "a": { "slug": "agentgate", "name": "AgentGate", "vendor": "Mohit Singh (mohitdebian)", "vendorUrl": "https://github.com/mohitdebian/AgentGate", "kind": "http-api", "category": "guardrails", "summary": "AgentGate is an open-source, self-hosted gateway that checks an agent's tool calls before they run. A small local classifier scores each call and a YAML policy returns allow, deny or ask, through a REST API or an MCP stdio wrapper.", "url": "https://www.anchorterminal.com/tools/agentgate", "markdownUrl": "https://www.anchorterminal.com/tools/agentgate.md", "slimMarkdownUrl": "https://www.anchorterminal.com/tools/agentgate.min.md", "jsonUrl": "https://www.anchorterminal.com/api/v1/tools/agentgate.json", "repo": "https://github.com/mohitdebian/AgentGate", "license": "MIT", "transports": [ "http", "stdio" ], "packages": [], "auth": "none", "authNotes": "No account. The agent endpoints (`/v1/sessions`, `/v1/assess`) are open unless the owner sets `AG_AGENT_KEY`, then need `Authorization: Bearer \u003ckey\u003e` or `x-agent-key`. Dashboard endpoints need `AG_DASHBOARD_KEY`, which falls back to `dev-key-123` when unset and is also accepted as a `?token=` query parameter. The checkpoint and shadow-summary endpoints have no auth check in the source.", "pricing": "free", "pricingNotes": "Free under MIT with nothing to buy. The owner runs four containers (Postgres, the Python decision service, the Fastify proxy and the dashboard), with an NVIDIA GPU recommended for the classifier and a CPU path in the code.", "priceSummary": "Free · OSS", "where": "local", "x402": { "level": "no", "evidence": "No x402, MPP or L402 in the source, the docs or the wiki (checked 2026-10-15). The project has no paid tier.", "endpoints": [] }, "toolCount": null, "popularity": { "githubStars": 0, "npmWeekly": null, "pypiWeekly": null, "asOf": "2026-10-15" }, "docsUrl": "https://github.com/mohitdebian/AgentGate/wiki/Client-Integration-Guide", "openapi": "https://github.com/mohitdebian/AgentGate/blob/main/docs/openapi.yaml", "capabilities": [ "guard.policy", "guard.injection", "guard.self-host" ], "tags": [ "open-source", "self-hosted", "local", "free", "no-card", "mit", "typescript", "python", "mcp", "docker", "openapi" ], "graded": true, "anchor": { "graded": true, "score": 48.5, "grade": "D", "agentReady": false, "rank": 883, "ranked": true, "rankOf": 1094, "categoryRank": 16, "methodology": "0.4", "run": "2026-10-01", "scores": { "ergonomics": 53, "maintenance": 28, "payments": 60, "reliability": 44, "schema": 47, "security": 49, "transparency": 56 }, "pending": [ "performance", "tasks" ], "assessment": { "confidence": "medium", "date": "2026-10-15" }, "negative": 0, "verdict": "An agent or its host can send each tool call to one REST endpoint, or wrap an MCP server, and get allow, deny or ask from a local classifier and a YAML policy, with an audit log and approval queue. The project is three days old, auth is off by default, and no detection accuracy is published.", "bestFor": "A team that wants a self-hosted check between an agent and its shell, database or webhook tools, with a human approval queue.", "strengths": [ "One documented call, `POST /v1/assess`, returns a verdict, reason codes and four head probabilities", "Fail-closed defaults. A model error or timeout falls back to ask, and unmatched tools default to ask", "Decisions are logged in Postgres with redacted arguments, a SHA-256 of the full arguments and approval reviewer notes", "MIT code and MIT model weights on Hugging Face with no gate, run entirely on the owner's machines", "Shadow mode and policy replay let an operator test a policy against past decisions before enforcing it" ], "weaknesses": [ "Agent endpoints need no key unless `AG_AGENT_KEY` is set, the proxy binds 0.0.0.0:8080, and the dashboard key defaults to `dev-key-123`", "Checkpoint revert, which runs git on the proxy's workspace, has no auth check in the source of 15 October 2026", "No tagged release, an empty changelog and version 0.1.0, three days after the first commit", "The MCP wrapper treats `allow_with_checkpoint` as an error and does not send the agent key to `/v1/assess`", "No published accuracy or false-positive rate for the classifier, trained in 60 steps per its model card" ], "agentNotes": [ "Create a session with the user's real goal first. The goal-alignment head scores every later call against it", "Pass earlier tool results in `history_override` with `untrusted: true` for web or email content, or the injection head sees only the action", "On `ask`, stop and tell the user the `decision_id`. Polling `/v1/decisions/:id` needs the dashboard key", "Treat `allow_with_checkpoint` as allow and keep the `checkpoint_id` for an undo", "Expect HTTP 404 with `not_found` for an unknown session and 401 when the owner has set an agent key" ], "metrics": { "kind": "local", "measured": false }, "reviewCount": 0, "avgRating": 0, "history": [ { "basis": "public evidence", "confidence": "medium", "grade": "D", "methodology": "0.4", "pending": [ "performance", "tasks" ], "run": "2026-10-01", "runLabel": "October 2026 research run", "score": 48.5 } ], "editorialScores": { "ergonomics": 53, "maintenance": 28, "payments": 60, "reliability": 44, "schema": 47, "security": 49, "transparency": 59 }, "provenanceScore": 53 }, "connect": { "install": "git clone https://github.com/mohitdebian/AgentGate.git \u0026\u0026 cd AgentGate \u0026\u0026 docker compose up -d", "http": "curl -s -X POST http://localhost:8080/v1/assess -H \"Content-Type: application/json\" -d '{\"session_id\":\"\u003cid from POST /v1/sessions\u003e\",\"action\":{\"tool\":\"bash_exec\",\"arguments\":{\"command\":\"rm -rf /var/www\"}}}'", "config": { "mcpServers": { "postgres": { "args": [ "/path/to/AgentGate/proxy/dist/src/mcp.js", "npx", "-y", "@modelcontextprotocol/server-postgres", "postgresql://user:pass@localhost:5432/production" ], "command": "node", "env": { "AGENTGATE_URL": "http://localhost:8080" } } } } }, "letme": { "capability": "https://letme.dev/guard.policy", "tool": "https://letme.dev/agentgate" }, "area": "models", "provenance": { "legalEntity": "Mohit Singh (individual)", "domain": "", "domainRegistered": "", "endpointOnVendorDomain": null, "terms": "", "privacy": "", "statusPage": "", "changelog": "https://github.com/mohitdebian/AgentGate/blob/main/CHANGELOG.md", "securityTxt": "none", "checked": "2026-10-15", "notes": [ "The licence file reads Copyright (c) 2026 Mohit Singh. The GitHub account mohitdebian links to mohitbuilds.in, a personal developer page.", "No terms or privacy policy. The software runs on the owner's machines, so there is no vendor endpoint or status page to check.", "SECURITY.md routes reports to GitHub private vulnerability reporting or a personal email, with a 48-hour acknowledgement target. No security.txt, since the project has no website.", "CHANGELOG.md holds a single Unreleased line, \"Initial scaffolding for Phase 1\"." ], "score": 53 }, "pageJsonUrl": "https://www.anchorterminal.com/tools/agentgate.json" }, "answer": "LlamaFirewall scores 50.8 (D) on agent readiness against AgentGate's 48.5 (D), and leads in 5 of 7 scored categories. AgentGate leads on payments \u0026 pricing and maintenance \u0026 community.", "b": { "slug": "llamafirewall", "name": "LlamaFirewall", "vendor": "Meta", "vendorUrl": "https://dev.meta.ai/llama/llama-protections", "kind": "framework", "category": "guardrails", "summary": "LlamaFirewall is Meta's open-source Python library for screening an AI agent's inputs, tool results and outputs. It runs scanners for prompt injection, hidden characters, insecure generated code and goal drift, and returns allow, block or human review.", "url": "https://www.anchorterminal.com/tools/llamafirewall", "markdownUrl": "https://www.anchorterminal.com/tools/llamafirewall.md", "slimMarkdownUrl": "https://www.anchorterminal.com/tools/llamafirewall.min.md", "jsonUrl": "https://www.anchorterminal.com/api/v1/tools/llamafirewall.json", "repo": "https://github.com/meta-llama/PurpleLlama/tree/main/LlamaFirewall", "license": "MIT (library). The Prompt Guard 2 weights it downloads are under the Llama 4 Community Licence", "transports": [], "packages": [ { "registry": "pypi", "name": "llamafirewall" } ], "auth": "none", "authNotes": "The library has no account or key of its own. The Prompt Guard scanner needs a Hugging Face token for an account Meta has approved for the gated `meta-llama/Llama-Prompt-Guard-2-86M` weights. AlignmentCheck and the PII scanner need `TOGETHER_API_KEY` for Together AI. The regex, hidden ASCII and CodeShield scanners need neither.", "pricing": "free", "pricingNotes": "Free under the MIT licence, with nothing to buy from Meta and no hosted version found. The cost is the owner's compute, plus Together AI's own charges when AlignmentCheck or the PII scanner is switched on. Those were not priced here.", "priceSummary": "Free · OSS", "where": "library", "x402": { "level": "no", "evidence": "No x402, MPP or L402 in the docs or the source. LlamaFirewall is a library the owner runs, with no payment route (checked 2026-10-08).", "endpoints": [] }, "toolCount": null, "popularity": { "githubStars": 4423, "npmWeekly": null, "pypiWeekly": 1029, "asOf": "2026-10-08" }, "docsUrl": "https://meta-llama.github.io/PurpleLlama/LlamaFirewall/", "capabilities": [ "guard.injection", "guard.pii", "guard.policy", "guard.self-host" ], "tags": [ "framework", "open-source", "self-hosted", "local", "python", "free", "gated", "no-telemetry", "stale-release" ], "lastRelease": "2025-05-29", "graded": true, "anchor": { "graded": true, "score": 50.8, "grade": "D", "agentReady": false, "rank": 828, "ranked": true, "rankOf": 1094, "categoryRank": 13, "methodology": "0.4", "run": "2026-10-01", "scores": { "ergonomics": 60, "maintenance": 15, "payments": 50, "reliability": 53, "schema": 49, "security": 56, "transparency": 58 }, "pending": [ "performance", "tasks" ], "assessment": { "confidence": "medium", "date": "2026-10-08" }, "negative": 0, "verdict": "One `scan()` call runs several checks on the owner's machine and returns a short typed result. The last PyPI release is 1.0.3 from 29 May 2025, and its Prompt Guard loader imports a `huggingface_hub` class that current versions no longer export, so a fresh install needs older pins. The classifier weights also need Meta's manual approval.", "bestFor": "A Python agent team that wants injection, hidden-character and generated-code checks in process, is willing to pin dependencies or install from main, and can get the gated weights.", "strengths": [ "Six scanner types sit behind one call, set per message role (user, assistant, tool, system, memory) in a plain mapping", "`ScanResult` is four typed fields (`decision`, `reason`, `score`, `status`), with decisions limited to allow, block or human review", "Prompt Guard, CodeShield, regex and hidden-character scanners run locally, and no telemetry code was found in the source", "MIT licence for the library, with tests run in public CI on Python 3.10 and 3.12 that passed on main on 29 September 2026", "`scan_replay` checks a whole conversation trace, and AlignmentCheck compares each agent step with the first user message" ], "weaknesses": [ "No PyPI release since 1.0.3 on 29 May 2025, and no changelog, tags or deprecation notes were found", "The 1.0.3 wheel imports `HfFolder` from `huggingface_hub`, which version 2.2.0 no longer exports. Main fixed the scanner on 26 March 2026, unreleased", "The Prompt Guard 2 weights are gated on Hugging Face with manual review, and the loader calls an interactive `login()` when no token is set", "Prompt Guard input is truncated at 512 tokens in the library, so later text in a long tool result is not scored", "AlignmentCheck and the PII scanner send the conversation to Together AI by default, and `create_scanner` passes no option to change the model or endpoint", "The custom scanner guide names a `BaseScanner` class that is not in the source, and LlamaFirewall issues from June and July 2025 have no reply" ], "agentNotes": [ "Pin `huggingface_hub` below 1.0 and a matching `transformers` 4.x before importing the Prompt Guard scanner from the 1.0.3 wheel, or install from main", "Get access to `meta-llama/Llama-Prompt-Guard-2-86M` and set a Hugging Face token first. Without one the loader prompts for a login and a headless run stalls", "Call `scan_async` inside a running event loop. `scan()` wraps `asyncio.run` and fails there. `scan_async` returns score 0.0 and reason `default` on every allow", "Split text longer than 512 tokens yourself before a Prompt Guard scan. The library truncates and does not chunk", "Do not feed a block `reason` back to the model. The Prompt Guard reason quotes the full scanned text, and the hidden ASCII reason decodes the hidden payload" ], "metrics": { "kind": "local", "measured": false }, "reviewCount": 0, "avgRating": 0, "history": [ { "basis": "public evidence", "confidence": "medium", "grade": "D", "methodology": "0.4", "pending": [ "performance", "tasks" ], "run": "2026-10-01", "runLabel": "October 2026 research run", "score": 50.8 } ], "editorialScores": { "ergonomics": 60, "maintenance": 15, "payments": 50, "reliability": 53, "schema": 49, "security": 56, "transparency": 56 }, "provenanceScore": 60 }, "connect": { "install": "pip install llamafirewall\nllamafirewall configure" }, "letme": { "capability": "https://letme.dev/guard.injection", "tool": "https://letme.dev/llamafirewall" }, "sameCompany": [ "llama-guard" ], "area": "models", "provenance": { "legalEntity": "Meta Platforms, Inc.", "domain": "llama.com", "domainRegistered": "1994-11-01", "domainNote": "A Python library the owner runs, not a service. Code is on github.com under the meta-llama organisation, docs on meta-llama.github.io, and Meta's Llama Protections page lists it.", "endpointOnVendorDomain": null, "terms": "", "privacy": "", "statusPage": "", "changelog": "", "securityTxt": "none", "checked": "2026-10-08", "notes": [ "The MIT licence in the LlamaFirewall folder is the document that governs use of the library, so it is recorded as the terms. Its copyright line reads Meta Platforms, Inc. and affiliates.", "The Prompt Guard 2 weights the library downloads are under the Llama 4 Community Licence, a separate document, and the repository root carries a Llama 3.2 licence file.", "No privacy policy governs the library, because the owner runs it. The privacy field is left out. The Hugging Face access form for the weights says details entered are handled under the Meta Privacy Policy.", "AlignmentCheck and the PII scanner send data to Together AI under the owner's own Together account. Meta publishes no data statement for that path.", "www.llama.com/llama-protections redirected to dev.meta.ai/llama/llama-protections on 8 October 2026, which names LlamaFirewall and links its paper. RDAP gives 1 November 1994 as the registration date of llama.com.", "No status page, because nothing is hosted. No changelog, release notes or version tags were found in the repository.", "security.txt returns 404 on meta-llama.github.io and dev.meta.ai. SECURITY.md in the LlamaFirewall folder sends reports to bugbounty.meta.com." ], "score": 60 }, "pageJsonUrl": "https://www.anchorterminal.com/tools/llamafirewall.json", "live": { "slug": "llamafirewall", "versions": [ { "registry": "pypi", "name": "llamafirewall", "version": "1.0.3", "released": "2025-05-29", "seenAt": "2026-10-15T00:02:47.08300975Z" } ], "githubStars": 4430, "pypiWeekly": 975, "securityTxt": { "url": "https://llama.com/.well-known/security.txt", "state": "none", "checkedAt": "2026-10-14T15:47:50.299736607Z" }, "domain": { "domain": "llama.com", "registered": "1994-11-01", "source": "https://rdap.verisign.com/com/v1/domain/llama.com", "checkedAt": "2026-10-11T13:13:11.472883251Z" }, "updatedAt": "2026-10-15T00:02:47.274868192Z" } }, "facts": [ { "a": "HTTP API", "b": "Agent framework", "name": "Kind" }, { "a": "Mohit Singh (mohitdebian)", "b": "Meta", "name": "Vendor" }, { "a": "no (local only)", "b": "no (local only)", "name": "Hosted endpoint" }, { "a": "HTTP, stdio", "b": "", "name": "Transports" }, { "a": "None", "b": "None", "name": "Auth" }, { "a": "Free", "b": "Free", "name": "Pricing" }, { "a": "no", "b": "no", "name": "x402" }, { "a": "MIT", "b": "MIT (library). The Prompt Guard 2 weights it downloads are under the Llama 4 Community Licence", "name": "Licence" }, { "a": "no", "b": "no", "name": "Read-only variant documented" }, { "a": "no", "b": "no", "name": "llms.txt" }, { "a": "none", "b": "2025-05-29", "name": "Last release" }, { "a": "no document linked", "b": "no document linked", "name": "Terms last updated" }, { "a": "no document linked", "b": "no document linked", "name": "Privacy policy last updated" }, { "a": "", "b": "", "name": "Customer content may train models" }, { "a": "", "b": "", "name": "Terms restrict automated access" }, { "a": "", "b": "", "name": "Terms restrict benchmarking" }, { "a": "", "b": "", "name": "Terms or service can change without notice" }, { "a": "", "b": "", "name": "Arbitration or class-action waiver" }, { "a": "0 stars", "b": "4.4k stars, 1k PyPI/wk", "name": "Popularity" } ], "faq": [ { "answer": "LlamaFirewall scores 50.8 (D) on agent readiness against AgentGate's 48.5 (D), and leads in 5 of 7 scored categories. AgentGate leads on payments \u0026 pricing and maintenance \u0026 community.", "question": "Which is better for AI agents, AgentGate or LlamaFirewall?" }, { "answer": "AgentGate runs on your own machine, with no hosted endpoint listed. No hosted endpoint is listed for LlamaFirewall.", "question": "Can an agent call AgentGate and LlamaFirewall without installing anything?" }, { "answer": "Yes. AgentGate is open source (MIT). LlamaFirewall is open source (MIT (library). The Prompt Guard 2 weights it downloads are under the Llama 4 Community Licence).", "question": "Are AgentGate and LlamaFirewall open source?" } ], "goodFor": [ { "aheadOn": [ "Payments \u0026 pricing, 60 against 50", "Maintenance \u0026 community, 28 against 15" ], "also": [ "Runs on your own machine", "Free to start without a card" ], "goodFor": "A team that wants a self-hosted check between an agent and its shell, database or webhook tools, with a human approval queue.", "slug": "agentgate", "watchFor": "Agent endpoints need no key unless `AG_AGENT_KEY` is set, the proxy binds 0.0.0.0:8080, and the dashboard key defaults to `dev-key-123`" }, { "aheadOn": [ "Reliability, 53 against 44", "Agent ergonomics, 60 against 53", "Security \u0026 auth, 56 against 49" ], "also": null, "goodFor": "A Python agent team that wants injection, hidden-character and generated-code checks in process, is willing to pin dependencies or install from main, and can get the gated weights.", "slug": "llamafirewall", "watchFor": "No PyPI release since 1.0.3 on 29 May 2025, and no changelog, tags or deprecation notes were found" } ], "job": { "capability": "guard.policy", "name": "Policy enforcement" }, "others": [ { "json": "https://www.anchorterminal.com/compare/amazon-bedrock-guardrails-vs-llamafirewall.json", "title": "Amazon Bedrock Guardrails vs LlamaFirewall", "url": "https://www.anchorterminal.com/compare/amazon-bedrock-guardrails-vs-llamafirewall" }, { "json": "https://www.anchorterminal.com/compare/azure-ai-content-safety-vs-llamafirewall.json", "title": "Azure AI Content Safety (Prompt Shields) vs LlamaFirewall", "url": "https://www.anchorterminal.com/compare/azure-ai-content-safety-vs-llamafirewall" }, { "json": "https://www.anchorterminal.com/compare/cisco-ai-defense-inspection-vs-llamafirewall.json", "title": "Cisco AI Defense Inspection API vs LlamaFirewall", "url": "https://www.anchorterminal.com/compare/cisco-ai-defense-inspection-vs-llamafirewall" }, { "json": "https://www.anchorterminal.com/compare/google-model-armor-vs-llamafirewall.json", "title": "Google Cloud Model Armor vs LlamaFirewall", "url": "https://www.anchorterminal.com/compare/google-model-armor-vs-llamafirewall" }, { "json": "https://www.anchorterminal.com/compare/granite-guardian-vs-llamafirewall.json", "title": "Granite Guardian vs LlamaFirewall", "url": "https://www.anchorterminal.com/compare/granite-guardian-vs-llamafirewall" }, { "json": "https://www.anchorterminal.com/compare/guardrails-ai-vs-llamafirewall.json", "title": "Guardrails AI vs LlamaFirewall", "url": "https://www.anchorterminal.com/compare/guardrails-ai-vs-llamafirewall" }, { "json": "https://www.anchorterminal.com/compare/lakera-guard-vs-llamafirewall.json", "title": "Lakera Guard (Check Point AI Guardrails) vs LlamaFirewall", "url": "https://www.anchorterminal.com/compare/lakera-guard-vs-llamafirewall" }, { "json": "https://www.anchorterminal.com/compare/llamafirewall-vs-nemo-guardrails.json", "title": "LlamaFirewall vs NVIDIA NeMo Guardrails", "url": "https://www.anchorterminal.com/compare/llamafirewall-vs-nemo-guardrails" }, { "json": "https://www.anchorterminal.com/compare/llamafirewall-vs-openai-guardrails.json", "title": "LlamaFirewall vs OpenAI Guardrails", "url": "https://www.anchorterminal.com/compare/llamafirewall-vs-openai-guardrails" }, { "json": "https://www.anchorterminal.com/compare/llamafirewall-vs-prisma-airs.json", "title": "LlamaFirewall vs Prisma AIRS AI Runtime Security API", "url": "https://www.anchorterminal.com/compare/llamafirewall-vs-prisma-airs" }, { "json": "https://www.anchorterminal.com/compare/agentgate-vs-amazon-bedrock-guardrails.json", "title": "AgentGate vs Amazon Bedrock Guardrails", "url": "https://www.anchorterminal.com/compare/agentgate-vs-amazon-bedrock-guardrails" }, { "json": "https://www.anchorterminal.com/compare/agentgate-vs-azure-ai-content-safety.json", "title": "AgentGate vs Azure AI Content Safety (Prompt Shields)", "url": "https://www.anchorterminal.com/compare/agentgate-vs-azure-ai-content-safety" }, { "json": "https://www.anchorterminal.com/compare/agentgate-vs-cisco-ai-defense-inspection.json", "title": "AgentGate vs Cisco AI Defense Inspection API", "url": "https://www.anchorterminal.com/compare/agentgate-vs-cisco-ai-defense-inspection" }, { "json": "https://www.anchorterminal.com/compare/agentgate-vs-google-model-armor.json", "title": "AgentGate vs Google Cloud Model Armor", "url": "https://www.anchorterminal.com/compare/agentgate-vs-google-model-armor" }, { "json": "https://www.anchorterminal.com/compare/agentgate-vs-granite-guardian.json", "title": "AgentGate vs Granite Guardian", "url": "https://www.anchorterminal.com/compare/agentgate-vs-granite-guardian" }, { "json": "https://www.anchorterminal.com/compare/agentgate-vs-guardrails-ai.json", "title": "AgentGate vs Guardrails AI", "url": "https://www.anchorterminal.com/compare/agentgate-vs-guardrails-ai" }, { "json": "https://www.anchorterminal.com/compare/agentgate-vs-lakera-guard.json", "title": "AgentGate vs Lakera Guard (Check Point AI Guardrails)", "url": "https://www.anchorterminal.com/compare/agentgate-vs-lakera-guard" }, { "json": "https://www.anchorterminal.com/compare/agentgate-vs-llama-guard.json", "title": "AgentGate vs Llama Guard 4", "url": "https://www.anchorterminal.com/compare/agentgate-vs-llama-guard" }, { "json": "https://www.anchorterminal.com/compare/agentgate-vs-mistral-moderation.json", "title": "AgentGate vs Mistral Moderation API", "url": "https://www.anchorterminal.com/compare/agentgate-vs-mistral-moderation" }, { "json": "https://www.anchorterminal.com/compare/agentgate-vs-nemo-guardrails.json", "title": "AgentGate vs NVIDIA NeMo Guardrails", "url": "https://www.anchorterminal.com/compare/agentgate-vs-nemo-guardrails" }, { "json": "https://www.anchorterminal.com/compare/agentgate-vs-openai-guardrails.json", "title": "AgentGate vs OpenAI Guardrails", "url": "https://www.anchorterminal.com/compare/agentgate-vs-openai-guardrails" }, { "json": "https://www.anchorterminal.com/compare/agentgate-vs-prisma-airs.json", "title": "AgentGate vs Prisma AIRS AI Runtime Security API", "url": "https://www.anchorterminal.com/compare/agentgate-vs-prisma-airs" }, { "json": "https://www.anchorterminal.com/compare/llama-guard-vs-llamafirewall.json", "title": "Llama Guard 4 vs LlamaFirewall", "url": "https://www.anchorterminal.com/compare/llama-guard-vs-llamafirewall" }, { "json": "https://www.anchorterminal.com/compare/llamafirewall-vs-microsoft-presidio.json", "title": "LlamaFirewall vs Presidio", "url": "https://www.anchorterminal.com/compare/llamafirewall-vs-microsoft-presidio" }, { "json": "https://www.anchorterminal.com/compare/llamafirewall-vs-mistral-moderation.json", "title": "LlamaFirewall vs Mistral Moderation API", "url": "https://www.anchorterminal.com/compare/llamafirewall-vs-mistral-moderation" }, { "json": "https://www.anchorterminal.com/compare/agentgate-vs-microsoft-presidio.json", "title": "AgentGate vs Presidio", "url": "https://www.anchorterminal.com/compare/agentgate-vs-microsoft-presidio" }, { "json": "https://www.anchorterminal.com/compare/llamafirewall-vs-openai-moderation.json", "title": "LlamaFirewall vs OpenAI Moderation API", "url": "https://www.anchorterminal.com/compare/llamafirewall-vs-openai-moderation" } ], "scores": [ { "agentgate": 44, "by": 9, "edge": "llamafirewall", "key": "reliability", "llamafirewall": 53, "name": "Reliability", "weight": 16 }, { "key": "performance", "name": "Performance", "pending": true, "weight": 10 }, { "agentgate": 47, "by": 2, "edge": "llamafirewall", "key": "schema", "llamafirewall": 49, "name": "Schema \u0026 documentation", "weight": 13 }, { "agentgate": 53, "by": 7, "edge": "llamafirewall", "key": "ergonomics", "llamafirewall": 60, "name": "Agent ergonomics", "weight": 13 }, { "agentgate": 49, "by": 7, "edge": "llamafirewall", "key": "security", "llamafirewall": 56, "name": "Security \u0026 auth", "weight": 14 }, { "agentgate": 60, "by": 10, "edge": "agentgate", "key": "payments", "llamafirewall": 50, "name": "Payments \u0026 pricing", "weight": 10 }, { "key": "tasks", "name": "Task success", "pending": true, "weight": 10 }, { "agentgate": 28, "by": 13, "edge": "agentgate", "key": "maintenance", "llamafirewall": 15, "name": "Maintenance \u0026 community", "weight": 7 }, { "agentgate": 56, "by": 2, "edge": "llamafirewall", "key": "transparency", "llamafirewall": 58, "name": "Transparency \u0026 trust", "weight": 7 } ], "summary": "LlamaFirewall scores 50.8 (D) on agent readiness against AgentGate's 48.5 (D), and leads in 5 of 7 scored categories. AgentGate leads on payments \u0026 pricing and maintenance \u0026 community. Both do policy enforcement.", "verdicts": { "agentgate": "An agent or its host can send each tool call to one REST endpoint, or wrap an MCP server, and get allow, deny or ask from a local classifier and a YAML policy, with an audit log and approval queue. The project is three days old, auth is off by default, and no detection accuracy is published.", "llamafirewall": "One `scan()` call runs several checks on the owner's machine and returns a short typed result. The last PyPI release is 1.0.3 from 29 May 2025, and its Prompt Guard loader imports a `huggingface_hub` class that current versions no longer export, so a fresh install needs older pins. The classifier weights also need Meta's manual approval." } }, "kind": "anchor.page", "links": { "api": "https://www.anchorterminal.com/api/v1/index.json", "html": "https://www.anchorterminal.com/compare/agentgate-vs-llamafirewall", "json": "https://www.anchorterminal.com/compare/agentgate-vs-llamafirewall.json", "llms": "https://www.anchorterminal.com/llms.txt", "markdown": "https://www.anchorterminal.com/compare/agentgate-vs-llamafirewall.md", "slim": "https://www.anchorterminal.com/compare/agentgate-vs-llamafirewall.min.md" }, "markdown": "LlamaFirewall scores 50.8 (D) on agent readiness against AgentGate's 48.5 (D), and leads in 5 of 7 scored categories. AgentGate leads on payments \u0026 pricing and maintenance \u0026 community. Both do policy enforcement.\n\n- AgentGate: grade D, 48.5/100, rank #883 of 1094. Markdown https://www.anchorterminal.com/tools/agentgate.md · JSON https://www.anchorterminal.com/api/v1/tools/agentgate.json\n- LlamaFirewall: grade D, 50.8/100, rank #828 of 1094. Markdown https://www.anchorterminal.com/tools/llamafirewall.md · JSON https://www.anchorterminal.com/api/v1/tools/llamafirewall.json\n- Best guardrails and safety filters for AI agents: https://www.anchorterminal.com/best/guardrails/index.md\n- All 132 guardrails comparisons: https://www.anchorterminal.com/compare/guardrails/index.md\n\n## Which one, for what\n\n### AgentGate (D)\n\nGood for: A team that wants a self-hosted check between an agent and its shell, database or webhook tools, with a human approval queue.\n\nAhead on:\n- Payments \u0026 pricing, 60 against 50\n- Maintenance \u0026 community, 28 against 15\n\nAlso in its favour:\n- Runs on your own machine\n- Free to start without a card\n\nWatch for: Agent endpoints need no key unless `AG_AGENT_KEY` is set, the proxy binds 0.0.0.0:8080, and the dashboard key defaults to `dev-key-123`\n\n### LlamaFirewall (D)\n\nGood for: A Python agent team that wants injection, hidden-character and generated-code checks in process, is willing to pin dependencies or install from main, and can get the gated weights.\n\nAhead on:\n- Reliability, 53 against 44\n- Agent ergonomics, 60 against 53\n- Security \u0026 auth, 56 against 49\n\nWatch for: No PyPI release since 1.0.3 on 29 May 2025, and no changelog, tags or deprecation notes were found\n\n\n## Score by category\n\n| Category | Weight | AgentGate | LlamaFirewall | Edge |\n| --- | --- | --- | --- | --- |\n| Reliability | 16% (20 this run) | 44 | 53 | LlamaFirewall +9 |\n| Performance | 10%, pending | pending | pending | not scored in this run |\n| Schema \u0026 documentation | 13% (16.2 this run) | 47 | 49 | LlamaFirewall +2 |\n| Agent ergonomics | 13% (16.2 this run) | 53 | 60 | LlamaFirewall +7 |\n| Security \u0026 auth | 14% (17.5 this run) | 49 | 56 | LlamaFirewall +7 |\n| Payments \u0026 pricing | 10% (12.5 this run) | 60 | 50 | AgentGate +10 |\n| Task success | 10%, pending | pending | pending | not scored in this run |\n| Maintenance \u0026 community | 7% (8.8 this run) | 28 | 15 | AgentGate +13 |\n| Transparency \u0026 trust | 7% (8.8 this run) | 56 | 58 | LlamaFirewall +2 |\n| Negative events | ≤15 | 0 | 0 | |\n| **Total** | | **48.5 · D** | **50.8 · D** | |\n\n## Facts side by side\n\n| Fact | AgentGate | LlamaFirewall |\n| --- | --- | --- |\n| Kind | HTTP API | Agent framework |\n| Vendor | Mohit Singh (mohitdebian) | Meta |\n| Hosted endpoint | no (local only) | no (local only) |\n| Transports | HTTP, stdio | |\n| Auth | None | None |\n| Pricing | Free | Free |\n| x402 | no | no |\n| Licence | MIT | MIT (library). The Prompt Guard 2 weights it downloads are under the Llama 4 Community Licence |\n| Read-only variant documented | no | no |\n| llms.txt | no | no |\n| Last release | none | 2025-05-29 |\n| Terms last updated | no document linked | no document linked |\n| Privacy policy last updated | no document linked | no document linked |\n| Customer content may train models | | |\n| Terms restrict automated access | | |\n| Terms restrict benchmarking | | |\n| Terms or service can change without notice | | |\n| Arbitration or class-action waiver | | |\n| Popularity | 0 stars | 4.4k stars, 1k PyPI/wk |\n\n## Verdicts\n\n**AgentGate.** An agent or its host can send each tool call to one REST endpoint, or wrap an MCP server, and get allow, deny or ask from a local classifier and a YAML policy, with an audit log and approval queue. The project is three days old, auth is off by default, and no detection accuracy is published.\n\n**LlamaFirewall.** One `scan()` call runs several checks on the owner's machine and returns a short typed result. The last PyPI release is 1.0.3 from 29 May 2025, and its Prompt Guard loader imports a `huggingface_hub` class that current versions no longer export, so a fresh install needs older pins. The classifier weights also need Meta's manual approval.\n\n## Before you call either\n\n### AgentGate\n\n1. Create a session with the user's real goal first. The goal-alignment head scores every later call against it\n2. Pass earlier tool results in `history_override` with `untrusted: true` for web or email content, or the injection head sees only the action\n3. On `ask`, stop and tell the user the `decision_id`. Polling `/v1/decisions/:id` needs the dashboard key\n4. Treat `allow_with_checkpoint` as allow and keep the `checkpoint_id` for an undo\n5. Expect HTTP 404 with `not_found` for an unknown session and 401 when the owner has set an agent key\n\n### LlamaFirewall\n\n1. Pin `huggingface_hub` below 1.0 and a matching `transformers` 4.x before importing the Prompt Guard scanner from the 1.0.3 wheel, or install from main\n2. Get access to `meta-llama/Llama-Prompt-Guard-2-86M` and set a Hugging Face token first. Without one the loader prompts for a login and a headless run stalls\n3. Call `scan_async` inside a running event loop. `scan()` wraps `asyncio.run` and fails there. `scan_async` returns score 0.0 and reason `default` on every allow\n4. Split text longer than 512 tokens yourself before a Prompt Guard scan. The library truncates and does not chunk\n5. Do not feed a block `reason` back to the model. The Prompt Guard reason quotes the full scanned text, and the hidden ASCII reason decodes the hidden payload\n\n## Questions\n\n### Which is better for AI agents, AgentGate or LlamaFirewall?\n\nLlamaFirewall scores 50.8 (D) on agent readiness against AgentGate's 48.5 (D), and leads in 5 of 7 scored categories. AgentGate leads on payments \u0026 pricing and maintenance \u0026 community.\n\n### Can an agent call AgentGate and LlamaFirewall without installing anything?\n\nAgentGate runs on your own machine, with no hosted endpoint listed. No hosted endpoint is listed for LlamaFirewall.\n\n### Are AgentGate and LlamaFirewall open source?\n\nYes. AgentGate is open source (MIT). LlamaFirewall is open source (MIT (library). The Prompt Guard 2 weights it downloads are under the Llama 4 Community Licence).\n\n\n## For agents\n\n- This comparison as JSON: https://www.anchorterminal.com/compare/agentgate-vs-llamafirewall.json, and with the fewest tokens: https://www.anchorterminal.com/compare/agentgate-vs-llamafirewall.min.md\n- Over MCP at https://www.anchorterminal.com/mcp (no key): `compare_tools {\"a\": \"agentgate\", \"b\": \"llamafirewall\"}`. From a terminal: `anchor compare agentgate llamafirewall`\n- Each listing in full: https://www.anchorterminal.com/api/v1/tools/agentgate.json and https://www.anchorterminal.com/api/v1/tools/llamafirewall.json\n\n## Other comparisons with AgentGate or LlamaFirewall\n\n- [Amazon Bedrock Guardrails vs LlamaFirewall](https://www.anchorterminal.com/compare/amazon-bedrock-guardrails-vs-llamafirewall.md)\n- [Azure AI Content Safety (Prompt Shields) vs LlamaFirewall](https://www.anchorterminal.com/compare/azure-ai-content-safety-vs-llamafirewall.md)\n- [Cisco AI Defense Inspection API vs LlamaFirewall](https://www.anchorterminal.com/compare/cisco-ai-defense-inspection-vs-llamafirewall.md)\n- [Google Cloud Model Armor vs LlamaFirewall](https://www.anchorterminal.com/compare/google-model-armor-vs-llamafirewall.md)\n- [Granite Guardian vs LlamaFirewall](https://www.anchorterminal.com/compare/granite-guardian-vs-llamafirewall.md)\n- [Guardrails AI vs LlamaFirewall](https://www.anchorterminal.com/compare/guardrails-ai-vs-llamafirewall.md)\n- [Lakera Guard (Check Point AI Guardrails) vs LlamaFirewall](https://www.anchorterminal.com/compare/lakera-guard-vs-llamafirewall.md)\n- [LlamaFirewall vs NVIDIA NeMo Guardrails](https://www.anchorterminal.com/compare/llamafirewall-vs-nemo-guardrails.md)\n- [LlamaFirewall vs OpenAI Guardrails](https://www.anchorterminal.com/compare/llamafirewall-vs-openai-guardrails.md)\n- [LlamaFirewall vs Prisma AIRS AI Runtime Security API](https://www.anchorterminal.com/compare/llamafirewall-vs-prisma-airs.md)\n- [AgentGate vs Amazon Bedrock Guardrails](https://www.anchorterminal.com/compare/agentgate-vs-amazon-bedrock-guardrails.md)\n- [AgentGate vs Azure AI Content Safety (Prompt Shields)](https://www.anchorterminal.com/compare/agentgate-vs-azure-ai-content-safety.md)\n- [AgentGate vs Cisco AI Defense Inspection API](https://www.anchorterminal.com/compare/agentgate-vs-cisco-ai-defense-inspection.md)\n- [AgentGate vs Google Cloud Model Armor](https://www.anchorterminal.com/compare/agentgate-vs-google-model-armor.md)\n- [AgentGate vs Granite Guardian](https://www.anchorterminal.com/compare/agentgate-vs-granite-guardian.md)\n- [AgentGate vs Guardrails AI](https://www.anchorterminal.com/compare/agentgate-vs-guardrails-ai.md)\n- [AgentGate vs Lakera Guard (Check Point AI Guardrails)](https://www.anchorterminal.com/compare/agentgate-vs-lakera-guard.md)\n- [AgentGate vs Llama Guard 4](https://www.anchorterminal.com/compare/agentgate-vs-llama-guard.md)\n- [AgentGate vs Mistral Moderation API](https://www.anchorterminal.com/compare/agentgate-vs-mistral-moderation.md)\n- [AgentGate vs NVIDIA NeMo Guardrails](https://www.anchorterminal.com/compare/agentgate-vs-nemo-guardrails.md)\n- [AgentGate vs OpenAI Guardrails](https://www.anchorterminal.com/compare/agentgate-vs-openai-guardrails.md)\n- [AgentGate vs Prisma AIRS AI Runtime Security API](https://www.anchorterminal.com/compare/agentgate-vs-prisma-airs.md)\n- [Llama Guard 4 vs LlamaFirewall](https://www.anchorterminal.com/compare/llama-guard-vs-llamafirewall.md)\n- [LlamaFirewall vs Presidio](https://www.anchorterminal.com/compare/llamafirewall-vs-microsoft-presidio.md)\n- [LlamaFirewall vs Mistral Moderation API](https://www.anchorterminal.com/compare/llamafirewall-vs-mistral-moderation.md)\n- [AgentGate vs Presidio](https://www.anchorterminal.com/compare/agentgate-vs-microsoft-presidio.md)\n- [LlamaFirewall vs OpenAI Moderation API](https://www.anchorterminal.com/compare/llamafirewall-vs-openai-moderation.md)\n", "meta": { "attribution": "Anchor Terminal (https://www.anchorterminal.com)", "attributionRequired": true, "credit": "CC BY 4.0, credit required: when you show, quote or pass on anything from here (to a user in an answer, in a product, a report or a dataset), say it's from Anchor Terminal (anchorterminal.com) and link the page or API address you took it from. Reviews also credit their author.", "docs": "https://www.anchorterminal.com/docs/", "generatedAt": "2026-10-15", "license": "CC-BY-4.0", "method": "https://www.anchorterminal.com/benchmark/", "methodology": "0.4", "openapi": "https://www.anchorterminal.com/openapi.json", "preview": false, "run": "2026-10-01", "runLabel": "October 2026 research run", "terms": "https://www.anchorterminal.com/terms/#data" }, "page": { "breadcrumbs": [ { "name": "Home", "url": "https://www.anchorterminal.com/" }, { "name": "Compare", "url": "https://www.anchorterminal.com/compare/" }, { "name": "AgentGate vs LlamaFirewall", "url": "" } ], "description": "LlamaFirewall scores 50.8 (D) to AgentGate's 48.5 (D) for policy enforcement. Prices, MCP, x402, uptime and agent notes side by side.", "facts": [ "AgentGate D 48.5", "LlamaFirewall D 50.8", "scores" ], "h1": "AgentGate vs LlamaFirewall", "image": "https://www.anchorterminal.com/assets/og/compare-agentgate-vs-llamafirewall.png", "path": "/compare/agentgate-vs-llamafirewall", "published": "2026-10-01", "section": "tools", "title": "AgentGate vs LlamaFirewall for AI agents in 2026: scores and prices", "toc": null, "updated": "2026-10-15", "url": "https://www.anchorterminal.com/compare/agentgate-vs-llamafirewall" }, "tokens": { "markdown": 2700, "slim": 580 }, "version": 1 }