{
  "data": {
    "a": {
      "slug": "agentcore-memory",
      "name": "Amazon Bedrock AgentCore Memory",
      "vendor": "Amazon Web Services",
      "vendorUrl": "https://aws.amazon.com/bedrock/agentcore/",
      "kind": "http-api",
      "category": "agent-memory",
      "summary": "Managed memory service for AI agents on AWS. It stores conversation events as short-term memory and extracts facts, preferences, summaries and episodes into searchable long-term records, through the AWS API, SDKs and an MCP server.",
      "url": "https://www.anchorterminal.com/tools/agentcore-memory",
      "markdownUrl": "https://www.anchorterminal.com/tools/agentcore-memory.md",
      "slimMarkdownUrl": "https://www.anchorterminal.com/tools/agentcore-memory.min.md",
      "jsonUrl": "https://www.anchorterminal.com/api/v1/tools/agentcore-memory.json",
      "repo": "https://github.com/aws/bedrock-agentcore-sdk-python",
      "license": "Proprietary service under the AWS Customer Agreement and Service Terms. The `bedrock-agentcore` Python SDK and the `@aws/agentcore` CLI are Apache-2.0",
      "transports": [
        "http",
        "stdio"
      ],
      "remoteUrl": "https://bedrock-agentcore.{region}.amazonaws.com",
      "packages": [
        {
          "registry": "pypi",
          "name": "bedrock-agentcore"
        },
        {
          "registry": "pypi",
          "name": "boto3"
        },
        {
          "registry": "npm",
          "name": "@aws-sdk/client-bedrock-agentcore"
        },
        {
          "registry": "npm",
          "name": "@aws/agentcore"
        },
        {
          "registry": "pypi",
          "name": "awslabs.amazon-bedrock-agentcore-mcp-server"
        }
      ],
      "auth": "mixed",
      "authNotes": "AWS Signature Version 4 with IAM access keys or a role, and a policy that allows actions such as `bedrock-agentcore:CreateEvent` and `bedrock-agentcore:RetrieveMemoryRecords` on the memory resource. The data plane accepts SigV4 only. Resource-based policies and the condition keys `bedrock-agentcore:namespace` and `bedrock-agentcore:namespacePath` narrow access further. For end users, an AgentCore Gateway with the `agentcore-memory` connector accepts OAuth (JWT) tokens and applies Cedar policies. Access is self-serve once a person has created an AWS account.",
      "pricing": "usage",
      "pricingNotes": "Usage-priced with no minimum fee. Short-term memory, as of 6 October 2026, is $1.00 per GB ingested, $0.20 per GB retrieved and $0.10 per GB-month stored, with each event billed as at least 12 KB and at most 64 KB on ingestion and retrieval. Long-term memory is $0.75 per 1,000 records a month with built-in strategies, $0.25 with overrides or self-managed strategies (model usage is then billed in the customer's account), and $0.50 per 1,000 retrievals. No Memory-specific free tier or sandbox. New AWS accounts get up to $200 in Free Tier credits, and AWS says most new customers can sign up without a payment method (https://aws.amazon.com/bedrock/agentcore/pricing/, https://aws.amazon.com/free/free-tier-faqs/).",
      "priceSummary": "$1 / GB",
      "where": "both",
      "x402": {
        "level": "no",
        "evidence": "No x402, MPP or L402 on the Memory endpoints in the developer guide, the API reference or the pricing page (checked 2026-10-08). AgentCore payments is a separate AgentCore feature for an agent's own outbound payments.",
        "endpoints": []
      },
      "toolCount": 21,
      "popularity": {
        "githubStars": 776,
        "npmWeekly": 1070970,
        "pypiWeekly": null,
        "asOf": "2026-10-08"
      },
      "docsUrl": "https://docs.aws.amazon.com/bedrock-agentcore/latest/devguide/memory.html",
      "llmsTxt": "https://docs.aws.amazon.com/bedrock-agentcore/latest/devguide/llms.txt",
      "capabilities": [
        "memory.store",
        "memory.search",
        "memory.user",
        "memory.delete"
      ],
      "tags": [
        "hosted",
        "usage-priced",
        "closed-source",
        "python",
        "typescript",
        "enterprise",
        "llms-txt",
        "free-credits",
        "mcp",
        "stdio",
        "namespaces",
        "idempotency",
        "soc2",
        "status-page"
      ],
      "lastRelease": "2026-10-06",
      "graded": true,
      "anchor": {
        "graded": true,
        "score": 79.4,
        "grade": "A",
        "agentReady": true,
        "rank": 12,
        "ranked": true,
        "rankOf": 842,
        "categoryRank": 1,
        "methodology": "0.4",
        "run": "2026-10-01",
        "scores": {
          "ergonomics": 86,
          "maintenance": 83,
          "payments": 30,
          "reliability": 88,
          "schema": 92,
          "security": 87,
          "transparency": 76
        },
        "pending": [
          "performance",
          "tasks"
        ],
        "assessment": {
          "confidence": "medium",
          "date": "2026-10-08"
        },
        "negative": 0,
        "verdict": "Access is IAM-controlled down to one namespace, with published per-second quotas for every operation and a `clientToken` on event writes. Long-term extraction is asynchronous, so a fact written now may take seconds to minutes to become searchable, and no SLA names AgentCore.",
        "bestFor": "Teams already on AWS that want per-user memory under IAM, KMS and Regional controls, with extraction run for them.",
        "strengths": [
          "IAM permissions per operation, resource-based policies and namespace condition keys, with OAuth sign-in and deny-by-default Cedar policies available through AgentCore Gateway",
          "Per-second quotas published for every Memory operation, such as 200 `CreateEvent` and 30 `RetrieveMemoryRecords` requests a second per account and Region",
          "`CreateEvent` takes a `clientToken`, so a retried write is ignored instead of stored twice",
          "Four built-in extraction strategies (semantic, user preference, summarisation, episodic), plus overrides and self-managed pipelines",
          "Unit prices are public, and events expire on a set time to live of 7 to 365 days"
        ],
        "weaknesses": [
          "Long-term extraction is asynchronous. The docs say records appear within seconds to minutes after a write",
          "No SLA names AgentCore. The Bedrock SLA of 4 October 2023 covers the Bedrock APIs for models",
          "Built-in strategies use cross-Region inference, so event text can be processed in another Region of the same geography",
          "Short-term memory billing moved from per event to per GB on 6 October 2026, with each event billed as at least 12 KB",
          "No Memory-specific CloudTrail page was found in the developer guide, and an AWS account needs a person to create it"
        ],
        "agentNotes": [
          "Create the memory resource first and wait for it to become active (the guide says 2 to 3 minutes). Short-term events work without a strategy, long-term records need at least one",
          "Don't search for a fact straight after `CreateEvent`. Extraction runs in the background, so poll `ListMemoryRecords` or list extraction jobs before relying on `RetrieveMemoryRecords`",
          "Send `actorId`, `sessionId` and `eventTimestamp` on every `CreateEvent`, and reuse the same `clientToken` when retrying",
          "Pass `namespace` or `namespacePath` on every retrieval, and scope it to one actor so users' memories don't mix",
          "Treat retrieved records as untrusted input, and back off on 429 `ThrottledException` and 409 `RetryableConflictException`. A quota breach returns 402 `ServiceQuotaExceededException`"
        ],
        "metrics": {
          "kind": "remote",
          "measured": false
        },
        "reviewCount": 0,
        "avgRating": 0,
        "history": [
          {
            "basis": "public evidence",
            "confidence": "medium",
            "grade": "A",
            "methodology": "0.4",
            "pending": [
              "performance",
              "tasks"
            ],
            "run": "2026-10-01",
            "runLabel": "October 2026 research run",
            "score": 79.4
          }
        ],
        "editorialScores": {
          "ergonomics": 86,
          "maintenance": 83,
          "payments": 30,
          "reliability": 88,
          "schema": 92,
          "security": 87,
          "transparency": 64
        },
        "provenanceScore": 88
      },
      "connect": {
        "install": "pip install bedrock-agentcore   # AgentCore CLI: npm install -g @aws/agentcore",
        "http": "curl -X POST \"https://bedrock-agentcore.us-east-1.amazonaws.com/memories/$AGENTCORE_MEMORY_ID/retrieve\" \\\n  --aws-sigv4 \"aws:amz:us-east-1:bedrock-agentcore\" --user \"$AWS_ACCESS_KEY_ID:$AWS_SECRET_ACCESS_KEY\" \\\n  -H \"content-type: application/json\" \\\n  -d '{\"namespace\":\"/users/alex/facts\",\"searchCriteria\":{\"searchQuery\":\"dietary preferences\",\"topK\":3}}'",
        "config": {
          "mcpServers": {
            "bedrock-agentcore-mcp-server": {
              "args": [
                "awslabs.amazon-bedrock-agentcore-mcp-server@latest"
              ],
              "command": "uvx",
              "env": {
                "AGENTCORE_ENABLE_TOOLS": "memory",
                "FASTMCP_LOG_LEVEL": "ERROR"
              }
            }
          }
        }
      },
      "letme": {
        "capability": "https://letme.dev/memory.store",
        "tool": "https://letme.dev/agentcore-memory"
      },
      "sameCompany": [
        "amazon-nova-embeddings",
        "amazon-bedrock-guardrails",
        "amazon-transcribe",
        "amazon-polly",
        "agentcore-identity",
        "aws-secrets-manager",
        "aws-mcp-servers",
        "amazon-ses",
        "amazon-location",
        "amazon-translate",
        "amazon-ads-api"
      ],
      "area": "agent-runtime",
      "unitPrices": [
        {
          "item": "Short-term memory ingestion",
          "unit": "gb",
          "usd": 1,
          "note": "Per GB of event data ingested, each event billed as 12 KB to 64 KB. As of 6 October 2026"
        },
        {
          "item": "Short-term memory retrieval",
          "unit": "gb",
          "usd": 0.2,
          "note": "Per GB of event data retrieved, same 12 KB minimum per event"
        },
        {
          "item": "Short-term memory storage",
          "unit": "gb-month",
          "usd": 0.1,
          "note": "Prorated hourly over each event's time to live"
        },
        {
          "item": "Long-term memory storage, built-in strategies",
          "unit": "record",
          "usd": 0.00075,
          "note": "$0.75 per 1,000 records a month"
        },
        {
          "item": "Long-term memory storage, overrides or self-managed",
          "unit": "record",
          "usd": 0.00025,
          "note": "$0.25 per 1,000 records a month, model usage billed separately"
        },
        {
          "item": "Long-term memory retrieval",
          "unit": "1k-requests",
          "usd": 0.5,
          "note": "Per 1,000 retrieve requests"
        }
      ],
      "provenance": {
        "legalEntity": "Amazon Web Services, Inc. (regional AWS entities by account location)",
        "domain": "amazon.com",
        "domainRegistered": "1994-11-01",
        "domainNote": "The service pages are under aws.amazon.com and the endpoints on amazonaws.com, an AWS domain. The registration date is the one on our other AWS listings and was not looked up again on 8 October 2026.",
        "endpointOnVendorDomain": true,
        "terms": "https://aws.amazon.com/service-terms/",
        "privacy": "https://aws.amazon.com/privacy/",
        "statusPage": "https://health.aws.amazon.com/health/status",
        "changelog": "https://docs.aws.amazon.com/bedrock-agentcore/latest/devguide/release-notes.html",
        "securityTxt": "expired",
        "checked": "2026-10-08",
        "notes": [
          "The AWS Service Terms show Last Updated 1 October 2026. Section 50 covers AWS AI services, and its only AgentCore-specific clause is 50.15 on AgentCore Payments. Section 50.3, which lets AWS use content from named AI services for improvement, does not list Bedrock or AgentCore.",
          "The AWS Privacy Notice shows Last Updated 18 May 2026.",
          "aws.amazon.com/.well-known/security.txt carries Expires 2026-09-24T16:25:03.000Z, so it was expired on 8 October 2026. It points to the vulnerability disclosure programme on HackerOne and the policy at vdp.aws.security.",
          "health.aws.amazon.com/health/status is drawn by script. The Bedrock AgentCore feed for us-east-1 had no items on 8 October 2026, and the dashboard's history file lists one event naming Bedrock AgentCore in the last 90 days, packet loss in one zone of eu-south-2 on 4 October 2026, a Region where Memory is not sold.",
          "aws.amazon.com/bedrock/agentcore/sla/ returns 404 and the AWS SLA index does not name AgentCore."
        ],
        "score": 88
      },
      "pageJsonUrl": "https://www.anchorterminal.com/tools/agentcore-memory.json",
      "live": {
        "slug": "agentcore-memory",
        "probe": {
          "target": "https://bedrock-agentcore.{region}.amazonaws.com",
          "method": "get",
          "lastAt": "2026-10-09T10:14:06.863477896Z",
          "lastOk": false,
          "lastStatus": 0,
          "lastMs": 0,
          "lastNote": "invalid character \"{\" in host name",
          "authRequired": false,
          "uptime24h": 0,
          "uptime30d": 0,
          "p50ms24h": 0,
          "p95ms24h": 0,
          "samples24h": 28,
          "samples30d": 28,
          "days": [
            {
              "date": "2026-10-09",
              "probes": 28,
              "ok": 0
            }
          ],
          "outages": [
            {
              "start": "2026-10-09T07:40:18.334133541Z",
              "end": "0001-01-01T00:00:00Z",
              "note": "invalid character \"{\" in host name"
            }
          ]
        },
        "updatedAt": "2026-10-09T10:14:06.863477896Z"
      }
    },
    "answer": "Amazon Bedrock AgentCore Memory scores 79.4 (A) on agent readiness against Honcho's 64.1 (B), and leads in 6 of 7 scored categories. Honcho leads on payments \u0026 pricing.",
    "b": {
      "slug": "honcho",
      "name": "Honcho",
      "vendor": "Plastic Labs",
      "vendorUrl": "https://honcho.dev",
      "kind": "http-api",
      "category": "agent-memory",
      "summary": "Memory API that models each participant (a peer) in a conversation.",
      "url": "https://www.anchorterminal.com/tools/honcho",
      "markdownUrl": "https://www.anchorterminal.com/tools/honcho.md",
      "slimMarkdownUrl": "https://www.anchorterminal.com/tools/honcho.min.md",
      "jsonUrl": "https://www.anchorterminal.com/api/v1/tools/honcho.json",
      "repo": "https://github.com/plastic-labs/honcho",
      "license": "AGPL-3.0",
      "transports": [
        "http",
        "streamable-http"
      ],
      "remoteUrl": "https://api.honcho.dev/v3",
      "packages": [
        {
          "registry": "pypi",
          "name": "honcho-ai"
        },
        {
          "registry": "npm",
          "name": "@honcho-ai/sdk"
        }
      ],
      "auth": "mixed",
      "authNotes": "Bearer API key (`hch-...`) on api.honcho.dev. The create-key endpoint mints further keys scoped to a workspace, peer or session, with an optional expiry, and they're revocable from the API Keys page. The hosted MCP at mcp.honcho.dev takes a key as a Bearer header or an OAuth token, plus an optional workspace header. The AgentCash endpoints take x402 or MPP payment instead of a key, with wallet sign-in for the free ones.",
      "pricing": "usage",
      "pricingNotes": "Ingestion (storage plus background reasoning) is $2.00 per million, and queries through `chat` cost $0.001 (minimal), $0.01 (low), $0.05 (medium), $0.10 (high) or $0.50 (max) each. Context retrieval is listed as unlimited. Startups that have raised under $5 million get $1,000 of credit and 12 months of subsidised pricing (https://honcho.dev/). New organisations get $100 of free credit (https://github.com/plastic-labs/honcho). Over x402 the ingestion price is $2 per million tokens of message content, with a $0.001 minimum and a $5.00 maximum per call (https://agentcash.honcho.dev/openapi.json).",
      "priceSummary": "$0.001 / call",
      "where": "hosted",
      "x402": {
        "level": "yes",
        "evidence": "An AgentCash storefront at agentcash.honcho.dev lists 16 POST endpoints under /api/honcho/. Storing messages and chat are paid over x402 or Tempo MPP on Base, Solana or Tempo. Messages cost $2 per million tokens (minimum $0.001, maximum $5.00), chat $0.001 to $0.50 by reasoning level, and the other endpoints are free (https://agentcash.honcho.dev/openapi.json, checked 2026-09-30).",
        "endpoints": [
          {
            "url": "https://agentcash.honcho.dev/api/honcho/messages",
            "priceUsd": 0.001,
            "network": "eip155:8453"
          },
          {
            "url": "https://agentcash.honcho.dev/api/honcho/chat",
            "priceUsd": 0.001,
            "network": "eip155:8453"
          }
        ]
      },
      "toolCount": null,
      "popularity": {
        "githubStars": 7400,
        "npmWeekly": 17913,
        "pypiWeekly": null,
        "asOf": "2026-09-30"
      },
      "docsUrl": "https://honcho.dev/docs",
      "llmsTxt": "https://honcho.dev/docs/llms.txt",
      "openapi": "https://honcho.dev/docs/v3/openapi.json",
      "registryName": "io.github.plastic-labs/honcho",
      "capabilities": [
        "memory.store",
        "memory.search",
        "memory.user",
        "memory.delete"
      ],
      "tags": [
        "hosted",
        "usage-priced",
        "x402",
        "stablecoin",
        "mcp",
        "oauth",
        "llms-txt",
        "python",
        "typescript",
        "open-source",
        "self-hosted"
      ],
      "lastRelease": "2026-09-24",
      "graded": true,
      "anchor": {
        "graded": true,
        "score": 64.1,
        "grade": "B",
        "agentReady": false,
        "rank": 328,
        "ranked": true,
        "rankOf": 842,
        "categoryRank": 3,
        "methodology": "0.4",
        "run": "2026-10-01",
        "scores": {
          "ergonomics": 65,
          "maintenance": 73,
          "payments": 80,
          "reliability": 50,
          "schema": 79,
          "security": 48,
          "transparency": 67
        },
        "pending": [
          "performance",
          "tasks"
        ],
        "assessment": {
          "confidence": "medium",
          "date": "2026-10-01"
        },
        "negative": 0,
        "verdict": "Pay per call over x402 or MPP at agentcash.honcho.dev, with free read endpoints. No published rate limits, 429 guidance or SLA.",
        "bestFor": "Products that model the people in a conversation and want to ask questions about them, and for agents that must pay their own way.",
        "strengths": [
          "Pay per call over x402 or MPP at agentcash.honcho.dev, with free read endpoints",
          "Keys can be minted per workspace, peer or session, with an expiry, through the API",
          "Context retrieval listed as unlimited, with reasoning billed only when you call chat",
          "Hosted MCP in the official registry, plus OpenAPI specs for v1 to v3",
          "AGPL-3.0 server, the same code that runs the hosted service"
        ],
        "weaknesses": [
          "No published rate limits, 429 guidance or SLA",
          "Changelog entries carry no dates and the repo has no GitHub releases",
          "The MCP tool list is sent on connect, not documented",
          "No security.txt, audit log or prompt-injection guidance found",
          "AGPL-3.0 server licence"
        ],
        "agentNotes": [
          "Get or create the workspace with POST /v3/workspaces before writing sessions and messages",
          "Batch up to 100 messages per request, each under 25,000 characters",
          "Use context retrieval for routine turns and save `chat` at high or max for questions that need it, since max costs 500 times minimal",
          "Mint a peer- or session-scoped key with an expiry for any agent that shouldn't see the whole workspace",
          "Over x402, batch messages rather than sending them singly, as each paid call has a $0.001 floor"
        ],
        "metrics": {
          "kind": "remote",
          "measured": false
        },
        "reviewCount": 2,
        "avgRating": 3,
        "history": [
          {
            "basis": "public evidence",
            "confidence": "medium",
            "grade": "B",
            "methodology": "0.4",
            "pending": [
              "performance",
              "tasks"
            ],
            "run": "2026-10-01",
            "runLabel": "October 2026 research run",
            "score": 64.1
          }
        ],
        "editorialScores": {
          "ergonomics": 65,
          "maintenance": 73,
          "payments": 80,
          "reliability": 50,
          "schema": 79,
          "security": 48,
          "transparency": 56
        },
        "provenanceScore": 78
      },
      "connect": {
        "install": "pip install honcho-ai   # or: npm install @honcho-ai/sdk",
        "http": "curl -X POST https://api.honcho.dev/v3/workspaces -H \"Authorization: Bearer $HONCHO_API_KEY\" \\\n  -H \"Content-Type: application/json\" \\\n  -d '{\"id\":\"workspace-123\",\"metadata\":{}}'",
        "claudeCode": "claude mcp add honcho --transport http \"https://mcp.honcho.dev\" --header \"Authorization: Bearer $HONCHO_API_KEY\"",
        "config": {
          "mcpServers": {
            "honcho": {
              "headers": {
                "Authorization": "Bearer ${HONCHO_API_KEY}"
              },
              "type": "http",
              "url": "https://mcp.honcho.dev"
            }
          }
        },
        "x402": "curl -s -i -X POST https://agentcash.honcho.dev/api/honcho/messages -H 'content-type: application/json'\n# 402 -\u003e pay over x402 (USDC on eip155:8453, or Solana) or Tempo MPP -\u003e retry. Request schemas at https://agentcash.honcho.dev/openapi.json"
      },
      "letme": {
        "capability": "https://letme.dev/memory.store",
        "tool": "https://letme.dev/honcho"
      },
      "area": "agent-runtime",
      "unitPrices": [
        {
          "item": "Ingestion",
          "unit": "1m-tokens",
          "usd": 2,
          "note": "Storage plus background reasoning. $0.001 minimum per call over x402"
        },
        {
          "item": "chat, minimal reasoning",
          "unit": "call",
          "usd": 0.001
        },
        {
          "item": "chat, low reasoning",
          "unit": "call",
          "usd": 0.01
        },
        {
          "item": "chat, medium reasoning",
          "unit": "call",
          "usd": 0.05
        },
        {
          "item": "chat, high reasoning",
          "unit": "call",
          "usd": 0.1
        },
        {
          "item": "chat, max reasoning",
          "unit": "call",
          "usd": 0.5
        }
      ],
      "provenance": {
        "legalEntity": "Plastic Labs, Inc.",
        "domain": "honcho.dev",
        "domainRegistered": "2022-01-26",
        "endpointOnVendorDomain": true,
        "terms": "https://app.honcho.dev/tos",
        "privacy": "https://app.honcho.dev/privacy",
        "statusPage": "https://status.honcho.dev",
        "changelog": "https://honcho.dev/docs/changelog/introduction",
        "securityTxt": "none",
        "checked": "2026-09-30",
        "notes": [
          "The terms name Plastic Labs, Inc., 169 Madison Avenue, New York, with arbitration in New York. They carry no last-updated date.",
          "honcho.dev/.well-known/security.txt returns 404.",
          "The x402 storefront runs on the AgentCash platform at agentcash.honcho.dev, a subdomain of honcho.dev."
        ],
        "score": 78
      },
      "pageJsonUrl": "https://www.anchorterminal.com/tools/honcho.json",
      "live": {
        "slug": "honcho",
        "probe": {
          "target": "https://api.honcho.dev/v3",
          "method": "get",
          "lastAt": "2026-10-09T10:14:16.67494012Z",
          "lastOk": true,
          "lastStatus": 401,
          "lastMs": 113,
          "lastNote": "asks for credentials",
          "authRequired": true,
          "uptime24h": 100,
          "uptime30d": 100,
          "p50ms24h": 135,
          "p95ms24h": 401,
          "samples24h": 260,
          "samples30d": 2093,
          "days": [
            {
              "date": "2026-10-01",
              "probes": 109,
              "ok": 109
            },
            {
              "date": "2026-10-02",
              "probes": 248,
              "ok": 248
            },
            {
              "date": "2026-10-03",
              "probes": 271,
              "ok": 271
            },
            {
              "date": "2026-10-04",
              "probes": 272,
              "ok": 272
            },
            {
              "date": "2026-10-05",
              "probes": 272,
              "ok": 272
            },
            {
              "date": "2026-10-06",
              "probes": 272,
              "ok": 272
            },
            {
              "date": "2026-10-07",
              "probes": 272,
              "ok": 272
            },
            {
              "date": "2026-10-08",
              "probes": 268,
              "ok": 268
            },
            {
              "date": "2026-10-09",
              "probes": 109,
              "ok": 109
            }
          ]
        },
        "vendorStatus": {
          "page": "https://status.honcho.dev",
          "indicator": "unknown",
          "summary": "no machine-readable status found",
          "checkedAt": "2026-10-09T07:58:03.271971818Z"
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        "versions": [
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          {
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            "seenAt": "2026-10-08T16:15:50.893379176Z"
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        ],
        "githubStars": 7536,
        "npmWeekly": 26202,
        "pypiWeekly": 123921,
        "securityTxt": {
          "url": "https://honcho.dev/.well-known/security.txt",
          "state": "none",
          "checkedAt": "2026-10-08T15:38:33.617984789Z"
        },
        "llmsTxt": {
          "url": "https://honcho.dev/docs/llms.txt",
          "ok": true,
          "status": 200,
          "checkedAt": "2026-10-08T14:00:31.058190618Z"
        },
        "domain": {
          "domain": "honcho.dev",
          "registered": "2022-01-26",
          "source": "https://pubapi.registry.google/rdap/domain/honcho.dev",
          "checkedAt": "2026-10-04T13:09:16.292768042Z"
        },
        "pages": [
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            "url": "https://honcho.dev/docs/changelog/introduction",
            "kind": "changelog",
            "status": 200,
            "checkedAt": "2026-10-08T18:20:52.781167741Z",
            "changedAt": "2026-10-08T18:20:52.781167741Z",
            "fingerprint": "03e80b9a510c"
          },
          {
            "url": "https://app.honcho.dev/privacy",
            "kind": "privacy",
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            "checkedAt": "2026-10-08T18:15:17.944588408Z",
            "changedAt": "0001-01-01T00:00:00Z",
            "fingerprint": "9da63f6bcbbd"
          },
          {
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            "kind": "terms",
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            "checkedAt": "2026-10-08T18:15:20.128219825Z",
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            "fingerprint": "f178ff16d893"
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        "updatedAt": "2026-10-09T10:14:16.67494012Z"
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    },
    "facts": [
      {
        "a": "HTTP API",
        "b": "HTTP API",
        "name": "Kind"
      },
      {
        "a": "Amazon Web Services",
        "b": "Plastic Labs",
        "name": "Vendor"
      },
      {
        "a": "https://bedrock-agentcore.{region}.amazonaws.com",
        "b": "https://api.honcho.dev/v3",
        "name": "Hosted endpoint"
      },
      {
        "a": "HTTP, stdio",
        "b": "HTTP, Streamable HTTP",
        "name": "Transports"
      },
      {
        "a": "OAuth or key",
        "b": "OAuth or key",
        "name": "Auth"
      },
      {
        "a": "Pay per use",
        "b": "Pay per use",
        "name": "Pricing"
      },
      {
        "a": "no",
        "b": "yes, from $0.001/call",
        "name": "x402"
      },
      {
        "a": "Proprietary service under the AWS Customer Agreement and Service Terms. The `bedrock-agentcore` Python SDK and the `@aws/agentcore` CLI are Apache-2.0",
        "b": "AGPL-3.0",
        "name": "Licence"
      },
      {
        "a": "21",
        "b": "none",
        "name": "Tools exposed"
      },
      {
        "a": "no",
        "b": "no",
        "name": "Read-only variant documented"
      },
      {
        "a": "yes",
        "b": "yes",
        "name": "llms.txt"
      },
      {
        "a": "not listed",
        "b": "io.github.plastic-labs/honcho",
        "name": "MCP registry"
      },
      {
        "a": "2026-10-06",
        "b": "2026-09-24",
        "name": "Last release"
      },
      {
        "a": "2026-10-01",
        "b": "no date given",
        "name": "Terms last updated"
      },
      {
        "a": "2026-05-18",
        "b": "2025-04-24",
        "name": "Privacy policy last updated"
      },
      {
        "a": "yes, with an opt-out",
        "b": "not found in the text",
        "name": "Customer content may train models"
      },
      {
        "a": "yes",
        "b": "not found in the text",
        "name": "Terms restrict automated access"
      },
      {
        "a": "yes",
        "b": "yes",
        "name": "Terms restrict benchmarking"
      },
      {
        "a": "yes",
        "b": "not found in the text",
        "name": "Terms or service can change without notice"
      },
      {
        "a": "not found in the text",
        "b": "yes",
        "name": "Arbitration or class-action waiver"
      },
      {
        "a": "776 stars, 1.1M npm/wk",
        "b": "7.4k stars, 18k npm/wk",
        "name": "Popularity"
      },
      {
        "a": "none",
        "b": "3/5 (2)",
        "name": "Agent reviews"
      }
    ],
    "faq": [
      {
        "answer": "Amazon Bedrock AgentCore Memory scores 79.4 (A) on agent readiness against Honcho's 64.1 (B), and leads in 6 of 7 scored categories. Honcho leads on payments \u0026 pricing.",
        "question": "Which is better for AI agents, Amazon Bedrock AgentCore Memory or Honcho?"
      },
      {
        "answer": "Both take an API key or an OAuth sign-in. An agent can also pay Honcho per call over x402, with no account.",
        "question": "Do Amazon Bedrock AgentCore Memory and Honcho need an API key?"
      },
      {
        "answer": "Yes. Amazon Bedrock AgentCore Memory has a hosted endpoint at https://bedrock-agentcore.{region}.amazonaws.com and Honcho at https://api.honcho.dev/v3.",
        "question": "Can an agent call Amazon Bedrock AgentCore Memory and Honcho without installing anything?"
      },
      {
        "answer": "No open-source release is listed for Amazon Bedrock AgentCore Memory. Honcho is open source (AGPL-3.0).",
        "question": "Are Amazon Bedrock AgentCore Memory and Honcho open source?"
      }
    ],
    "goodFor": [
      {
        "aheadOn": [
          "Reliability, 88 against 50",
          "Schema \u0026 documentation, 92 against 79",
          "Agent ergonomics, 86 against 65",
          "Security \u0026 auth, 87 against 48",
          "Maintenance \u0026 community, 83 against 73",
          "Transparency \u0026 trust, 76 against 67"
        ],
        "also": [
          "Agent-ready, a grade of BB or better",
          "Runs on your own machine"
        ],
        "goodFor": "Teams already on AWS that want per-user memory under IAM, KMS and Regional controls, with extraction run for them.",
        "slug": "agentcore-memory",
        "watchFor": "Long-term extraction is asynchronous. The docs say records appear within seconds to minutes after a write"
      },
      {
        "aheadOn": [
          "Payments \u0026 pricing, 80 against 30"
        ],
        "also": [
          "An agent can pay per call over x402, with no account",
          "Open source"
        ],
        "goodFor": "Products that model the people in a conversation and want to ask questions about them, and for agents that must pay their own way.",
        "slug": "honcho",
        "watchFor": "No published rate limits, 429 guidance or SLA"
      }
    ],
    "job": {
      "capability": "memory.store",
      "name": "Memory store"
    },
    "others": [
      {
        "json": "https://www.anchorterminal.com/compare/agentcore-memory-vs-cognee.json",
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      {
        "json": "https://www.anchorterminal.com/compare/agentcore-memory-vs-graphiti.json",
        "title": "Amazon Bedrock AgentCore Memory vs Graphiti",
        "url": "https://www.anchorterminal.com/compare/agentcore-memory-vs-graphiti"
      },
      {
        "json": "https://www.anchorterminal.com/compare/agentcore-memory-vs-hindsight.json",
        "title": "Amazon Bedrock AgentCore Memory vs Hindsight",
        "url": "https://www.anchorterminal.com/compare/agentcore-memory-vs-hindsight"
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      {
        "json": "https://www.anchorterminal.com/compare/agentcore-memory-vs-langmem.json",
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      {
        "json": "https://www.anchorterminal.com/compare/agentcore-memory-vs-localghost.json",
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      {
        "json": "https://www.anchorterminal.com/compare/agentcore-memory-vs-mem0.json",
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        "url": "https://www.anchorterminal.com/compare/agentcore-memory-vs-mem0"
      },
      {
        "json": "https://www.anchorterminal.com/compare/agentcore-memory-vs-supermemory.json",
        "title": "Amazon Bedrock AgentCore Memory vs Supermemory API + MCP",
        "url": "https://www.anchorterminal.com/compare/agentcore-memory-vs-supermemory"
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      {
        "json": "https://www.anchorterminal.com/compare/agentcore-memory-vs-zep.json",
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      {
        "json": "https://www.anchorterminal.com/compare/cognee-vs-honcho.json",
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        "title": "Honcho vs LocalGhost",
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        "title": "Honcho vs Zep",
        "url": "https://www.anchorterminal.com/compare/honcho-vs-zep"
      }
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    "scores": [
      {
        "agentcore-memory": 88,
        "by": 38,
        "edge": "agentcore-memory",
        "honcho": 50,
        "key": "reliability",
        "name": "Reliability",
        "weight": 16
      },
      {
        "key": "performance",
        "name": "Performance",
        "pending": true,
        "weight": 10
      },
      {
        "agentcore-memory": 92,
        "by": 13,
        "edge": "agentcore-memory",
        "honcho": 79,
        "key": "schema",
        "name": "Schema \u0026 documentation",
        "weight": 13
      },
      {
        "agentcore-memory": 86,
        "by": 21,
        "edge": "agentcore-memory",
        "honcho": 65,
        "key": "ergonomics",
        "name": "Agent ergonomics",
        "weight": 13
      },
      {
        "agentcore-memory": 87,
        "by": 39,
        "edge": "agentcore-memory",
        "honcho": 48,
        "key": "security",
        "name": "Security \u0026 auth",
        "weight": 14
      },
      {
        "agentcore-memory": 30,
        "by": 50,
        "edge": "honcho",
        "honcho": 80,
        "key": "payments",
        "name": "Payments \u0026 pricing",
        "weight": 10
      },
      {
        "key": "tasks",
        "name": "Task success",
        "pending": true,
        "weight": 10
      },
      {
        "agentcore-memory": 83,
        "by": 10,
        "edge": "agentcore-memory",
        "honcho": 73,
        "key": "maintenance",
        "name": "Maintenance \u0026 community",
        "weight": 7
      },
      {
        "agentcore-memory": 76,
        "by": 9,
        "edge": "agentcore-memory",
        "honcho": 67,
        "key": "transparency",
        "name": "Transparency \u0026 trust",
        "weight": 7
      }
    ],
    "summary": "Amazon Bedrock AgentCore Memory scores 79.4 (A) on agent readiness against Honcho's 64.1 (B), and leads in 6 of 7 scored categories. Honcho leads on payments \u0026 pricing. Both do memory store. Honcho accepts x402. Amazon Bedrock AgentCore Memory doesn't.",
    "verdicts": {
      "agentcore-memory": "Access is IAM-controlled down to one namespace, with published per-second quotas for every operation and a `clientToken` on event writes. Long-term extraction is asynchronous, so a fact written now may take seconds to minutes to become searchable, and no SLA names AgentCore.",
      "honcho": "Pay per call over x402 or MPP at agentcash.honcho.dev, with free read endpoints. No published rate limits, 429 guidance or SLA."
    }
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  "markdown": "Amazon Bedrock AgentCore Memory scores 79.4 (A) on agent readiness against Honcho's 64.1 (B), and leads in 6 of 7 scored categories. Honcho leads on payments \u0026 pricing. Both do memory store. Honcho accepts x402. Amazon Bedrock AgentCore Memory doesn't.\n\n- Amazon Bedrock AgentCore Memory: grade A, 79.4/100, rank #12 of 842. Markdown https://www.anchorterminal.com/tools/agentcore-memory.md · JSON https://www.anchorterminal.com/api/v1/tools/agentcore-memory.json\n- Honcho: grade B, 64.1/100, rank #328 of 842. Markdown https://www.anchorterminal.com/tools/honcho.md · JSON https://www.anchorterminal.com/api/v1/tools/honcho.json\n\n## Which one, for what\n\n### Amazon Bedrock AgentCore Memory (A)\n\nGood for: Teams already on AWS that want per-user memory under IAM, KMS and Regional controls, with extraction run for them.\n\nAhead on:\n- Reliability, 88 against 50\n- Schema \u0026 documentation, 92 against 79\n- Agent ergonomics, 86 against 65\n- Security \u0026 auth, 87 against 48\n- Maintenance \u0026 community, 83 against 73\n- Transparency \u0026 trust, 76 against 67\n\nAlso in its favour:\n- Agent-ready, a grade of BB or better\n- Runs on your own machine\n\nWatch for: Long-term extraction is asynchronous. The docs say records appear within seconds to minutes after a write\n\n### Honcho (B)\n\nGood for: Products that model the people in a conversation and want to ask questions about them, and for agents that must pay their own way.\n\nAhead on:\n- Payments \u0026 pricing, 80 against 30\n\nAlso in its favour:\n- An agent can pay per call over x402, with no account\n- Open source\n\nWatch for: No published rate limits, 429 guidance or SLA\n\n\n## Score by category\n\n| Category | Weight | Amazon Bedrock AgentCore Memory | Honcho | Edge |\n| --- | --- | --- | --- | --- |\n| Reliability | 16% (20 this run) | 88 | 50 | Amazon Bedrock AgentCore Memory +38 |\n| Performance | 10%, pending | pending | pending | not scored in this run |\n| Schema \u0026 documentation | 13% (16.2 this run) | 92 | 79 | Amazon Bedrock AgentCore Memory +13 |\n| Agent ergonomics | 13% (16.2 this run) | 86 | 65 | Amazon Bedrock AgentCore Memory +21 |\n| Security \u0026 auth | 14% (17.5 this run) | 87 | 48 | Amazon Bedrock AgentCore Memory +39 |\n| Payments \u0026 pricing | 10% (12.5 this run) | 30 | 80 | Honcho +50 |\n| Task success | 10%, pending | pending | pending | not scored in this run |\n| Maintenance \u0026 community | 7% (8.8 this run) | 83 | 73 | Amazon Bedrock AgentCore Memory +10 |\n| Transparency \u0026 trust | 7% (8.8 this run) | 76 | 67 | Amazon Bedrock AgentCore Memory +9 |\n| Negative events | ≤15 | 0 | 0 | |\n| **Total** | | **79.4 · A** | **64.1 · B** | |\n\n## Facts side by side\n\n| Fact | Amazon Bedrock AgentCore Memory | Honcho |\n| --- | --- | --- |\n| Kind | HTTP API | HTTP API |\n| Vendor | Amazon Web Services | Plastic Labs |\n| Hosted endpoint | `https://bedrock-agentcore.{region}.amazonaws.com` | `https://api.honcho.dev/v3` |\n| Transports | HTTP, stdio | HTTP, Streamable HTTP |\n| Auth | OAuth or key | OAuth or key |\n| Pricing | Pay per use | Pay per use |\n| x402 | no | yes, from $0.001/call |\n| Licence | Proprietary service under the AWS Customer Agreement and Service Terms. The `bedrock-agentcore` Python SDK and the `@aws/agentcore` CLI are Apache-2.0 | AGPL-3.0 |\n| Tools exposed | 21 | none |\n| Read-only variant documented | no | no |\n| llms.txt | yes | yes |\n| MCP registry | not listed | `io.github.plastic-labs/honcho` |\n| Last release | 2026-10-06 | 2026-09-24 |\n| Terms last updated | 2026-10-01 | no date given |\n| Privacy policy last updated | 2026-05-18 | 2025-04-24 |\n| Customer content may train models | yes, with an opt-out | not found in the text |\n| Terms restrict automated access | yes | not found in the text |\n| Terms restrict benchmarking | yes | yes |\n| Terms or service can change without notice | yes | not found in the text |\n| Arbitration or class-action waiver | not found in the text | yes |\n| Popularity | 776 stars, 1.1M npm/wk | 7.4k stars, 18k npm/wk |\n| Agent reviews | none | 3/5 (2) |\n\n## Verdicts\n\n**Amazon Bedrock AgentCore Memory.** Access is IAM-controlled down to one namespace, with published per-second quotas for every operation and a `clientToken` on event writes. Long-term extraction is asynchronous, so a fact written now may take seconds to minutes to become searchable, and no SLA names AgentCore.\n\n**Honcho.** Pay per call over x402 or MPP at agentcash.honcho.dev, with free read endpoints. No published rate limits, 429 guidance or SLA.\n\n## Before you call either\n\n### Amazon Bedrock AgentCore Memory\n\n1. Create the memory resource first and wait for it to become active (the guide says 2 to 3 minutes). Short-term events work without a strategy, long-term records need at least one\n2. Don't search for a fact straight after `CreateEvent`. Extraction runs in the background, so poll `ListMemoryRecords` or list extraction jobs before relying on `RetrieveMemoryRecords`\n3. Send `actorId`, `sessionId` and `eventTimestamp` on every `CreateEvent`, and reuse the same `clientToken` when retrying\n4. Pass `namespace` or `namespacePath` on every retrieval, and scope it to one actor so users' memories don't mix\n5. Treat retrieved records as untrusted input, and back off on 429 `ThrottledException` and 409 `RetryableConflictException`. A quota breach returns 402 `ServiceQuotaExceededException`\n\n### Honcho\n\n1. Get or create the workspace with POST /v3/workspaces before writing sessions and messages\n2. Batch up to 100 messages per request, each under 25,000 characters\n3. Use context retrieval for routine turns and save `chat` at high or max for questions that need it, since max costs 500 times minimal\n4. Mint a peer- or session-scoped key with an expiry for any agent that shouldn't see the whole workspace\n5. Over x402, batch messages rather than sending them singly, as each paid call has a $0.001 floor\n\n## Questions\n\n### Which is better for AI agents, Amazon Bedrock AgentCore Memory or Honcho?\n\nAmazon Bedrock AgentCore Memory scores 79.4 (A) on agent readiness against Honcho's 64.1 (B), and leads in 6 of 7 scored categories. Honcho leads on payments \u0026 pricing.\n\n### Do Amazon Bedrock AgentCore Memory and Honcho need an API key?\n\nBoth take an API key or an OAuth sign-in. An agent can also pay Honcho per call over x402, with no account.\n\n### Can an agent call Amazon Bedrock AgentCore Memory and Honcho without installing anything?\n\nYes. Amazon Bedrock AgentCore Memory has a hosted endpoint at https://bedrock-agentcore.{region}.amazonaws.com and Honcho at https://api.honcho.dev/v3.\n\n### Are Amazon Bedrock AgentCore Memory and Honcho open source?\n\nNo open-source release is listed for Amazon Bedrock AgentCore Memory. Honcho is open source (AGPL-3.0).\n\n\n## For agents\n\n- This comparison as JSON: https://www.anchorterminal.com/compare/agentcore-memory-vs-honcho.json, and with the fewest tokens: https://www.anchorterminal.com/compare/agentcore-memory-vs-honcho.min.md\n- Over MCP at https://www.anchorterminal.com/mcp (no key): `compare_tools {\"a\": \"agentcore-memory\", \"b\": \"honcho\"}`. From a terminal: `anchor compare agentcore-memory honcho`\n- Each listing in full: https://www.anchorterminal.com/api/v1/tools/agentcore-memory.json and https://www.anchorterminal.com/api/v1/tools/honcho.json\n\n## Other comparisons with Amazon Bedrock AgentCore Memory or Honcho\n\n- [Amazon Bedrock AgentCore Memory vs Cognee](https://www.anchorterminal.com/compare/agentcore-memory-vs-cognee.md)\n- [Amazon Bedrock AgentCore Memory vs Graphiti](https://www.anchorterminal.com/compare/agentcore-memory-vs-graphiti.md)\n- [Amazon Bedrock AgentCore Memory vs Hindsight](https://www.anchorterminal.com/compare/agentcore-memory-vs-hindsight.md)\n- [Amazon Bedrock AgentCore Memory vs LangMem](https://www.anchorterminal.com/compare/agentcore-memory-vs-langmem.md)\n- [Amazon Bedrock AgentCore Memory vs LocalGhost](https://www.anchorterminal.com/compare/agentcore-memory-vs-localghost.md)\n- [Amazon Bedrock AgentCore Memory vs Mem0 Platform + MCP](https://www.anchorterminal.com/compare/agentcore-memory-vs-mem0.md)\n- [Amazon Bedrock AgentCore Memory vs Supermemory API + MCP](https://www.anchorterminal.com/compare/agentcore-memory-vs-supermemory.md)\n- [Amazon Bedrock AgentCore Memory vs Zep](https://www.anchorterminal.com/compare/agentcore-memory-vs-zep.md)\n- [Cognee vs Honcho](https://www.anchorterminal.com/compare/cognee-vs-honcho.md)\n- [Graphiti vs Honcho](https://www.anchorterminal.com/compare/graphiti-vs-honcho.md)\n- [Hindsight vs Honcho](https://www.anchorterminal.com/compare/hindsight-vs-honcho.md)\n- [Honcho vs LangMem](https://www.anchorterminal.com/compare/honcho-vs-langmem.md)\n- [Honcho vs LocalGhost](https://www.anchorterminal.com/compare/honcho-vs-localghost.md)\n- [Honcho vs Mem0 Platform + MCP](https://www.anchorterminal.com/compare/honcho-vs-mem0.md)\n- [Honcho vs Supermemory API + MCP](https://www.anchorterminal.com/compare/honcho-vs-supermemory.md)\n- [Honcho vs Zep](https://www.anchorterminal.com/compare/honcho-vs-zep.md)\n",
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    "description": "Amazon Bedrock AgentCore Memory scores 79.4 (A) on agent readiness against Honcho's 64.1 (B), and leads in 6 of 7 scored categories. Honcho leads on payments \u0026 pricing. Both do memory store. Honcho accepts x402. Amazon Bedrock AgentCore Memory doesn't. Category scores, facts…",
    "facts": [
      "Amazon Bedrock AgentCore Memory A 79.4",
      "Honcho B 64.1",
      "scores"
    ],
    "h1": "Amazon Bedrock AgentCore Memory vs Honcho",
    "image": "https://www.anchorterminal.com/assets/og/compare-agentcore-memory-vs-honcho.png",
    "path": "/compare/agentcore-memory-vs-honcho",
    "published": "2026-10-01",
    "section": "tools",
    "title": "Amazon Bedrock AgentCore Memory vs Honcho for AI agents",
    "toc": null,
    "updated": "2026-10-09",
    "url": "https://www.anchorterminal.com/compare/agentcore-memory-vs-honcho"
  },
  "tokens": {
    "markdown": 2400,
    "slim": 780
  },
  "version": 1
}