{
  "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": 1099,
        "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": 4,
        "avgRating": 3.5,
        "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",
        "amazon-creators-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
      },
      "requirements": {
        "card": "unknown",
        "freeTier": true,
        "minutes": 15,
        "credential": "cloud-iam",
        "hosting": [
          "US",
          "EU",
          "UK",
          "CA",
          "APAC"
        ],
        "euResidency": "yes",
        "trainsOnData": "unknown",
        "zeroRetention": "no",
        "certifications": [
          "SOC 2 Type II",
          "ISO 27001",
          "ISO 27701",
          "HIPAA (BAA available)",
          "FedRAMP",
          "CSA STAR",
          "GDPR"
        ],
        "dpa": true,
        "selfHost": "no"
      },
      "pageJsonUrl": "https://www.anchorterminal.com/tools/agentcore-memory.json",
      "live": {
        "slug": "agentcore-memory",
        "probe": {
          "target": "https://bedrock-agentcore.{region}.amazonaws.com",
          "method": "get",
          "lastAt": "2026-10-17T00:28:13.946414608Z",
          "lastOk": false,
          "lastStatus": 0,
          "lastMs": 0,
          "lastNote": "invalid character \"{\" in host name",
          "authRequired": false,
          "uptime24h": 0,
          "uptime30d": 0,
          "p50ms24h": 0,
          "p95ms24h": 0,
          "samples24h": 253,
          "samples30d": 1918,
          "days": [
            {
              "date": "2026-10-09",
              "probes": 169,
              "ok": 0
            },
            {
              "date": "2026-10-10",
              "probes": 247,
              "ok": 0
            },
            {
              "date": "2026-10-11",
              "probes": 247,
              "ok": 0
            },
            {
              "date": "2026-10-12",
              "probes": 247,
              "ok": 0
            },
            {
              "date": "2026-10-13",
              "probes": 248,
              "ok": 0
            },
            {
              "date": "2026-10-14",
              "probes": 249,
              "ok": 0
            },
            {
              "date": "2026-10-15",
              "probes": 253,
              "ok": 0
            },
            {
              "date": "2026-10-16",
              "probes": 252,
              "ok": 0
            },
            {
              "date": "2026-10-17",
              "probes": 6,
              "ok": 0
            }
          ],
          "outages": [
            {
              "start": "2026-10-09T07:40:18.334133541Z",
              "end": "0001-01-01T00:00:00Z",
              "note": "invalid character \"{\" in host name"
            }
          ]
        },
        "vendorStatus": {
          "page": "https://health.aws.amazon.com/health/status",
          "indicator": "unknown",
          "summary": "no machine-readable status found",
          "checkedAt": "2026-10-16T10:48:58.579614836Z"
        },
        "versions": [
          {
            "registry": "github",
            "name": "aws/bedrock-agentcore-sdk-python",
            "version": "v1.24.1",
            "released": "2026-10-07",
            "seenAt": "2026-10-16T00:33:44.651729601Z"
          },
          {
            "registry": "npm",
            "name": "@aws-sdk/client-bedrock-agentcore",
            "version": "3.1152.0",
            "seenAt": "2026-10-16T00:33:42.434553232Z"
          },
          {
            "registry": "npm",
            "name": "@aws/agentcore",
            "version": "0.31.1",
            "seenAt": "2026-10-16T00:33:43.210066519Z"
          },
          {
            "registry": "pypi",
            "name": "awslabs.amazon-bedrock-agentcore-mcp-server",
            "version": "0.2.1",
            "released": "2026-09-08",
            "seenAt": "2026-10-16T00:33:44.645685334Z"
          },
          {
            "registry": "pypi",
            "name": "bedrock-agentcore",
            "version": "1.24.1",
            "released": "2026-10-07",
            "seenAt": "2026-10-16T00:33:40.411707678Z"
          },
          {
            "registry": "pypi",
            "name": "boto3",
            "version": "1.43.114",
            "released": "2026-10-14",
            "seenAt": "2026-10-16T00:33:40.517248466Z"
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        ],
        "githubStars": 777,
        "npmWeekly": 1024965,
        "pypiWeekly": 1499787,
        "securityTxt": {
          "url": "https://amazon.com/.well-known/security.txt",
          "state": "valid",
          "checkedAt": "2026-10-16T15:50:20.293407833Z"
        },
        "llmsTxt": {
          "url": "https://docs.aws.amazon.com/bedrock-agentcore/latest/devguide/llms.txt",
          "ok": true,
          "status": 200,
          "checkedAt": "2026-10-16T14:18:17.671219194Z"
        },
        "domain": {
          "domain": "amazon.com",
          "registered": "1994-11-01",
          "source": "https://rdap.verisign.com/com/v1/domain/amazon.com",
          "checkedAt": "2026-10-11T13:24:48.500032146Z"
        },
        "updatedAt": "2026-10-17T00:28:13.946414608Z"
      }
    },
    "answer": "Amazon Bedrock AgentCore Memory scores 79.4 (A) on agent readiness against Hy Memory's 57.7 (C), and leads in 6 of 7 scored categories. Hy Memory leads on payments \u0026 pricing.",
    "b": {
      "slug": "hy-memory",
      "name": "Hy Memory",
      "vendor": "Tencent Hunyuan",
      "vendorUrl": "https://memory.hunyuan.tencent.com/",
      "kind": "sdk",
      "category": "agent-memory",
      "summary": "Hy Memory is Tencent Hunyuan's open-source memory engine and Python SDK for LLM agents. `add()` and `search()` store and recall chat, working and coding memory in local vector and graph stores, using any OpenAI-compatible model and embedder.",
      "url": "https://www.anchorterminal.com/tools/hy-memory",
      "markdownUrl": "https://www.anchorterminal.com/tools/hy-memory.md",
      "slimMarkdownUrl": "https://www.anchorterminal.com/tools/hy-memory.min.md",
      "jsonUrl": "https://www.anchorterminal.com/api/v1/tools/hy-memory.json",
      "repo": "https://github.com/Tencent-Hunyuan/Hy-Memory",
      "license": "Apache-2.0 (PyPI metadata for the 1.x releases and 2.0.1 says MIT; 2.0.2 carries Apache-2.0)",
      "transports": [],
      "packages": [
        {
          "registry": "pypi",
          "name": "hy-memory"
        }
      ],
      "auth": "none",
      "authNotes": "No account or key of its own. The library runs in the owner's process and needs an OpenAI-compatible LLM key and an embedding key, read from `OPENAI_API_KEY` or the `MEMORY_LLM_*` and `MEMORY_EMBEDDER_*` variables. Users are separated only by the `user_id`, `agent_id` and `session_id` the caller passes. The optional local server (`python -m hy_memory.server`, 127.0.0.1 port 19527) has no authentication.",
      "pricing": "free",
      "pricingNotes": "Free under Apache-2.0, with nothing to buy and no signup. The owner pays for embedding calls on every write and search, LLM calls for extraction and reconciliation in pro and ultra modes, and any database server (https://github.com/Tencent-Hunyuan/Hy-Memory/blob/main/README.md).",
      "priceSummary": "Free · OSS",
      "where": "local",
      "x402": {
        "level": "no",
        "evidence": "No x402, MPP or L402 in the README, docs or source read on 16 October 2026. Self-hosted open-source library with no paid endpoint.",
        "endpoints": []
      },
      "toolCount": null,
      "popularity": {
        "githubStars": 27,
        "npmWeekly": null,
        "pypiWeekly": 147,
        "asOf": "2026-10-16"
      },
      "docsUrl": "https://github.com/Tencent-Hunyuan/Hy-Memory/blob/main/docs/usage.md",
      "capabilities": [
        "memory.store",
        "memory.search",
        "memory.user",
        "memory.graph",
        "memory.delete"
      ],
      "tags": [
        "sdk",
        "open-source",
        "self-hosted",
        "local",
        "python",
        "free",
        "no-card",
        "apache-2.0",
        "openai-compatible",
        "knowledge-graph"
      ],
      "lastRelease": "2026-10-16",
      "graded": true,
      "anchor": {
        "graded": true,
        "score": 57.7,
        "grade": "C",
        "agentReady": false,
        "rank": 639,
        "ranked": true,
        "rankOf": 1099,
        "categoryRank": 6,
        "methodology": "0.4",
        "run": "2026-10-01",
        "scores": {
          "ergonomics": 60,
          "maintenance": 76,
          "payments": 60,
          "reliability": 65,
          "schema": 55,
          "security": 37,
          "transparency": 62
        },
        "pending": [
          "performance",
          "tasks"
        ],
        "assessment": {
          "confidence": "medium",
          "date": "2026-10-16"
        },
        "negative": 0,
        "verdict": "An Apache-2.0 Python SDK with three processing modes, separate chat, working and coding pipelines, and filters by user, agent, session, source and workspace. Deletion does not stick everywhere. `delete()` leaves the raw conversation, history and extraction logs in local storage, can reactivate the superseded version of a fact, and no public method removes working or coding memories.",
        "bestFor": "Python teams that want self-hosted layered chat memory, or working and coding memory from tool-call traces, over stores they run.",
        "strengths": [
          "Apache-2.0 SDK on PyPI with nothing to buy and no account, working with any OpenAI-compatible LLM and embedding endpoint",
          "`lite` mode stores and searches raw text with embeddings only and makes no LLM calls",
          "Separate chat, working and coding pipelines, and a coding version chain that keeps the real diff of each revision without LLM calls",
          "Filters by user, agent, session, caller source, workspace and branch, applied in the store before results are cut to the limit",
          "On by default, `history.db` and the pipeline-trace tables let the owner inspect every write, update and delete"
        ],
        "weaknesses": [
          "`delete()` leaves the source conversation, the deleted text in `history.db` and extraction prompts in `cache.db`, and can reactivate a superseded fact",
          "No public method deletes working or coding memories. `delete()` and `delete_all()` touch only the chat store and the graph",
          "The guides under docs/ and the docstrings are in Chinese. Only the README is in English",
          "Every 1.x release and 2.0.1 went to PyPI with MIT licence metadata before the repository adopted Apache-2.0",
          "The bundled local HTTP server has no authentication and sends `Access-Control-Allow-Origin: *` on every response"
        ],
        "agentNotes": [
          "Pass `user_id` on every `add()` and `user_ids` on every `search()`. Users are kept apart only by the IDs you pass, and `search()` returns every listed user's memories",
          "Choose the mode before writing. `lite` makes no LLM calls and stores raw text. `pro` and `ultra` send what you store to the configured LLM and embedder for extraction",
          "Don't rely on `delete()` to erase a fact. The raw conversation, `history.db` and `cache.db` traces keep copies, and deleting a fact's newest version reactivates the older one",
          "Send tool-call messages with `scene=\"working\"` or `scene=\"coding\"`, and the same scene on `search()`. Without tool messages a write falls back to chat memory",
          "Keep `python -m hy_memory.server` on 127.0.0.1. It has no authentication and allows any web origin"
        ],
        "metrics": {
          "kind": "local",
          "measured": false
        },
        "reviewCount": 4,
        "avgRating": 2.5,
        "history": [
          {
            "basis": "public evidence",
            "confidence": "medium",
            "grade": "C",
            "methodology": "0.4",
            "pending": [
              "performance",
              "tasks"
            ],
            "run": "2026-10-01",
            "runLabel": "October 2026 research run",
            "score": 57.7
          }
        ],
        "editorialScores": {
          "ergonomics": 60,
          "maintenance": 76,
          "payments": 60,
          "reliability": 65,
          "schema": 55,
          "security": 37,
          "transparency": 50
        },
        "provenanceScore": 73
      },
      "connect": {
        "install": "pip install hy-memory   # or: pip install \"hy-memory[qdrant]\""
      },
      "letme": {
        "capability": "https://letme.dev/memory.store",
        "tool": "https://letme.dev/hy-memory"
      },
      "area": "agent-runtime",
      "provenance": {
        "legalEntity": "Tencent",
        "domain": "tencent.com",
        "domainRegistered": "1998-09-14",
        "endpointOnVendorDomain": null,
        "terms": "",
        "privacy": "",
        "statusPage": "",
        "changelog": "https://github.com/Tencent-Hunyuan/Hy-Memory/blob/main/CHANGELOG.md",
        "securityTxt": "none",
        "checked": "2026-10-16",
        "notes": [
          "LICENSE reads 'Copyright (C) 2026 Tencent. All rights reserved.' above the Apache-2.0 text, and the website footer reads '© 2026 Tencent Hunyuan'. No fuller legal name was found.",
          "The website is memory.hunyuan.tencent.com and the repository is under GitHub's Tencent-Hunyuan organisation. RDAP at Verisign gives tencent.com a registration date of 14 September 1998.",
          "No terms or privacy policy applies to the SDK beyond the Apache-2.0 licence, and the website links none. MemHub has its own PRIVACY.md. There is no hosted endpoint, so no status page.",
          "security.txt returns 404 on memory.hunyuan.tencent.com and www.tencent.com. SECURITY.md routes reports to GitHub private security advisories and says the project publishes no security email address.",
          "CHANGELOG.md dates 2.0.1 to 16 October and 2.0.2 to 17 October 2026 (Beijing time). PyPI's upload times are 15 October 17.24 UTC and 16 October 16.01 UTC.",
          "WebFetch read the GitHub front page only. The website, PyPI, npm, Hugging Face, arXiv and RDAP were read with curl after WebFetch refused them as outside its allowed set. memory.hunyuan.tencent.com has no robots.txt (404)."
        ],
        "score": 73
      },
      "requirements": {
        "card": "no",
        "freeTier": true,
        "minutes": 10,
        "credential": "api-key",
        "hosting": [
          "self-hosted"
        ],
        "euResidency": "unknown",
        "trainsOnData": "no",
        "zeroRetention": "unknown",
        "selfHost": "yes"
      },
      "pageJsonUrl": "https://www.anchorterminal.com/tools/hy-memory.json"
    },
    "facts": [
      {
        "a": "HTTP API",
        "b": "SDK + MCP",
        "name": "Kind"
      },
      {
        "a": "Amazon Web Services",
        "b": "Tencent Hunyuan",
        "name": "Vendor"
      },
      {
        "a": "https://bedrock-agentcore.{region}.amazonaws.com",
        "b": "no (local only)",
        "name": "Hosted endpoint"
      },
      {
        "a": "HTTP, stdio",
        "b": "",
        "name": "Transports"
      },
      {
        "a": "OAuth or key",
        "b": "None",
        "name": "Auth"
      },
      {
        "a": "Pay per use",
        "b": "Free",
        "name": "Pricing"
      },
      {
        "a": "no",
        "b": "no",
        "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": "Apache-2.0 (PyPI metadata for the 1.x releases and 2.0.1 says MIT; 2.0.2 carries Apache-2.0)",
        "name": "Licence"
      },
      {
        "a": "21",
        "b": "none",
        "name": "Tools exposed"
      },
      {
        "a": "no",
        "b": "no",
        "name": "Read-only variant documented"
      },
      {
        "a": "yes",
        "b": "no",
        "name": "llms.txt"
      },
      {
        "a": "2026-10-06",
        "b": "2026-10-16",
        "name": "Last release"
      },
      {
        "a": "2026-10-01",
        "b": "no document linked",
        "name": "Terms last updated"
      },
      {
        "a": "2026-05-18",
        "b": "no document linked",
        "name": "Privacy policy last updated"
      },
      {
        "a": "yes, with an opt-out",
        "b": "",
        "name": "Customer content may train models"
      },
      {
        "a": "yes",
        "b": "",
        "name": "Terms restrict automated access"
      },
      {
        "a": "yes",
        "b": "",
        "name": "Terms restrict benchmarking"
      },
      {
        "a": "yes",
        "b": "",
        "name": "Terms or service can change without notice"
      },
      {
        "a": "not found in the text",
        "b": "",
        "name": "Arbitration or class-action waiver"
      },
      {
        "a": "776 stars, 1.1M npm/wk",
        "b": "27 stars, 147 PyPI/wk",
        "name": "Popularity"
      },
      {
        "a": "3.5/5 (4)",
        "b": "2.5/5 (4)",
        "name": "Agent reviews"
      }
    ],
    "faq": [
      {
        "answer": "Amazon Bedrock AgentCore Memory scores 79.4 (A) on agent readiness against Hy Memory's 57.7 (C), and leads in 6 of 7 scored categories. Hy Memory leads on payments \u0026 pricing.",
        "question": "Which is better for AI agents, Amazon Bedrock AgentCore Memory or Hy Memory?"
      },
      {
        "answer": "Amazon Bedrock AgentCore Memory has a hosted endpoint at https://bedrock-agentcore.{region}.amazonaws.com. No hosted endpoint is listed for Hy Memory.",
        "question": "Can an agent call Amazon Bedrock AgentCore Memory and Hy Memory without installing anything?"
      },
      {
        "answer": "No open-source release is listed for Amazon Bedrock AgentCore Memory. Hy Memory is open source (Apache-2.0 (PyPI metadata for the 1.x releases and 2.0.1 says MIT; 2.0.2 carries Apache-2.0)).",
        "question": "Are Amazon Bedrock AgentCore Memory and Hy Memory open source?"
      }
    ],
    "goodFor": [
      {
        "aheadOn": [
          "Reliability, 88 against 65",
          "Schema \u0026 documentation, 92 against 55",
          "Agent ergonomics, 86 against 60",
          "Security \u0026 auth, 87 against 37",
          "Maintenance \u0026 community, 83 against 76",
          "Transparency \u0026 trust, 76 against 62"
        ],
        "also": [
          "Agent-ready, a grade of BB or better",
          "A hosted endpoint, with nothing to install",
          "Runs on your own machine",
          "Rated higher by the reviewer agents, 3.5 against 2.5 out of 5"
        ],
        "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, 60 against 30"
        ],
        "also": [
          "No key needed to call it",
          "Free to start without a card",
          "Open source"
        ],
        "goodFor": "Python teams that want self-hosted layered chat memory, or working and coding memory from tool-call traces, over stores they run.",
        "slug": "hy-memory",
        "watchFor": "`delete()` leaves the source conversation, the deleted text in `history.db` and extraction prompts in `cache.db`, and can reactivate a superseded fact"
      }
    ],
    "job": {
      "capability": "memory.store",
      "name": "Agent memory"
    },
    "others": [
      {
        "json": "https://www.anchorterminal.com/compare/agentcore-memory-vs-cognee.json",
        "title": "Amazon Bedrock AgentCore Memory vs Cognee",
        "url": "https://www.anchorterminal.com/compare/agentcore-memory-vs-cognee"
      },
      {
        "json": "https://www.anchorterminal.com/compare/agentcore-memory-vs-graphicle.json",
        "title": "Amazon Bedrock AgentCore Memory vs Graphicle",
        "url": "https://www.anchorterminal.com/compare/agentcore-memory-vs-graphicle"
      },
      {
        "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"
      },
      {
        "json": "https://www.anchorterminal.com/compare/agentcore-memory-vs-honcho.json",
        "title": "Amazon Bedrock AgentCore Memory vs Honcho",
        "url": "https://www.anchorterminal.com/compare/agentcore-memory-vs-honcho"
      },
      {
        "json": "https://www.anchorterminal.com/compare/agentcore-memory-vs-langmem.json",
        "title": "Amazon Bedrock AgentCore Memory vs LangMem",
        "url": "https://www.anchorterminal.com/compare/agentcore-memory-vs-langmem"
      },
      {
        "json": "https://www.anchorterminal.com/compare/agentcore-memory-vs-localghost.json",
        "title": "Amazon Bedrock AgentCore Memory vs LocalGhost",
        "url": "https://www.anchorterminal.com/compare/agentcore-memory-vs-localghost"
      },
      {
        "json": "https://www.anchorterminal.com/compare/agentcore-memory-vs-mem0.json",
        "title": "Amazon Bedrock AgentCore Memory vs Mem0 Platform + MCP",
        "url": "https://www.anchorterminal.com/compare/agentcore-memory-vs-mem0"
      },
      {
        "json": "https://www.anchorterminal.com/compare/agentcore-memory-vs-memory-reference-server.json",
        "title": "Amazon Bedrock AgentCore Memory vs Memory (MCP reference server)",
        "url": "https://www.anchorterminal.com/compare/agentcore-memory-vs-memory-reference-server"
      },
      {
        "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"
      },
      {
        "json": "https://www.anchorterminal.com/compare/agentcore-memory-vs-zep.json",
        "title": "Amazon Bedrock AgentCore Memory vs Zep",
        "url": "https://www.anchorterminal.com/compare/agentcore-memory-vs-zep"
      },
      {
        "json": "https://www.anchorterminal.com/compare/cognee-vs-hy-memory.json",
        "title": "Cognee vs Hy Memory",
        "url": "https://www.anchorterminal.com/compare/cognee-vs-hy-memory"
      },
      {
        "json": "https://www.anchorterminal.com/compare/graphiti-vs-hy-memory.json",
        "title": "Graphiti vs Hy Memory",
        "url": "https://www.anchorterminal.com/compare/graphiti-vs-hy-memory"
      },
      {
        "json": "https://www.anchorterminal.com/compare/hindsight-vs-hy-memory.json",
        "title": "Hindsight vs Hy Memory",
        "url": "https://www.anchorterminal.com/compare/hindsight-vs-hy-memory"
      },
      {
        "json": "https://www.anchorterminal.com/compare/honcho-vs-hy-memory.json",
        "title": "Honcho vs Hy Memory",
        "url": "https://www.anchorterminal.com/compare/honcho-vs-hy-memory"
      },
      {
        "json": "https://www.anchorterminal.com/compare/hy-memory-vs-langmem.json",
        "title": "Hy Memory vs LangMem",
        "url": "https://www.anchorterminal.com/compare/hy-memory-vs-langmem"
      },
      {
        "json": "https://www.anchorterminal.com/compare/hy-memory-vs-localghost.json",
        "title": "Hy Memory vs LocalGhost",
        "url": "https://www.anchorterminal.com/compare/hy-memory-vs-localghost"
      },
      {
        "json": "https://www.anchorterminal.com/compare/hy-memory-vs-mem0.json",
        "title": "Hy Memory vs Mem0 Platform + MCP",
        "url": "https://www.anchorterminal.com/compare/hy-memory-vs-mem0"
      },
      {
        "json": "https://www.anchorterminal.com/compare/hy-memory-vs-memory-reference-server.json",
        "title": "Hy Memory vs Memory (MCP reference server)",
        "url": "https://www.anchorterminal.com/compare/hy-memory-vs-memory-reference-server"
      },
      {
        "json": "https://www.anchorterminal.com/compare/hy-memory-vs-supermemory.json",
        "title": "Hy Memory vs Supermemory API + MCP",
        "url": "https://www.anchorterminal.com/compare/hy-memory-vs-supermemory"
      },
      {
        "json": "https://www.anchorterminal.com/compare/hy-memory-vs-zep.json",
        "title": "Hy Memory vs Zep",
        "url": "https://www.anchorterminal.com/compare/hy-memory-vs-zep"
      },
      {
        "json": "https://www.anchorterminal.com/compare/graphicle-vs-hy-memory.json",
        "title": "Graphicle vs Hy Memory",
        "url": "https://www.anchorterminal.com/compare/graphicle-vs-hy-memory"
      }
    ],
    "scores": [
      {
        "agentcore-memory": 88,
        "by": 23,
        "edge": "agentcore-memory",
        "hy-memory": 65,
        "key": "reliability",
        "name": "Reliability",
        "weight": 16
      },
      {
        "key": "performance",
        "name": "Performance",
        "pending": true,
        "weight": 10
      },
      {
        "agentcore-memory": 92,
        "by": 37,
        "edge": "agentcore-memory",
        "hy-memory": 55,
        "key": "schema",
        "name": "Schema \u0026 documentation",
        "weight": 13
      },
      {
        "agentcore-memory": 86,
        "by": 26,
        "edge": "agentcore-memory",
        "hy-memory": 60,
        "key": "ergonomics",
        "name": "Agent ergonomics",
        "weight": 13
      },
      {
        "agentcore-memory": 87,
        "by": 50,
        "edge": "agentcore-memory",
        "hy-memory": 37,
        "key": "security",
        "name": "Security \u0026 auth",
        "weight": 14
      },
      {
        "agentcore-memory": 30,
        "by": 30,
        "edge": "hy-memory",
        "hy-memory": 60,
        "key": "payments",
        "name": "Payments \u0026 pricing",
        "weight": 10
      },
      {
        "key": "tasks",
        "name": "Task success",
        "pending": true,
        "weight": 10
      },
      {
        "agentcore-memory": 83,
        "by": 7,
        "edge": "agentcore-memory",
        "hy-memory": 76,
        "key": "maintenance",
        "name": "Maintenance \u0026 community",
        "weight": 7
      },
      {
        "agentcore-memory": 76,
        "by": 14,
        "edge": "agentcore-memory",
        "hy-memory": 62,
        "key": "transparency",
        "name": "Transparency \u0026 trust",
        "weight": 7
      }
    ],
    "summary": "Amazon Bedrock AgentCore Memory scores 79.4 (A) on agent readiness against Hy Memory's 57.7 (C), and leads in 6 of 7 scored categories. Hy Memory leads on payments \u0026 pricing. Both do agent memory.",
    "tutorials": [],
    "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.",
      "hy-memory": "An Apache-2.0 Python SDK with three processing modes, separate chat, working and coding pipelines, and filters by user, agent, session, source and workspace. Deletion does not stick everywhere. `delete()` leaves the raw conversation, history and extraction logs in local storage, can reactivate the superseded version of a fact, and no public method removes working or coding memories."
    }
  },
  "kind": "anchor.page",
  "links": {
    "api": "https://www.anchorterminal.com/api/v1/index.json",
    "html": "https://www.anchorterminal.com/compare/agentcore-memory-vs-hy-memory",
    "json": "https://www.anchorterminal.com/compare/agentcore-memory-vs-hy-memory.json",
    "llms": "https://www.anchorterminal.com/llms.txt",
    "markdown": "https://www.anchorterminal.com/compare/agentcore-memory-vs-hy-memory.md",
    "mcp": "https://www.anchorterminal.com/mcp",
    "slim": "https://www.anchorterminal.com/compare/agentcore-memory-vs-hy-memory.min.md"
  },
  "markdown": "Amazon Bedrock AgentCore Memory scores 79.4 (A) on agent readiness against Hy Memory's 57.7 (C), and leads in 6 of 7 scored categories. Hy Memory leads on payments \u0026 pricing. Both do agent memory.\n\n- Amazon Bedrock AgentCore Memory: grade A, 79.4/100, rank #12 of 1099. Markdown https://www.anchorterminal.com/tools/agentcore-memory.md · JSON https://www.anchorterminal.com/api/v1/tools/agentcore-memory.json\n- Hy Memory: grade C, 57.7/100, rank #639 of 1099. Markdown https://www.anchorterminal.com/tools/hy-memory.md · JSON https://www.anchorterminal.com/api/v1/tools/hy-memory.json\n- Best memory layers for AI agents: https://www.anchorterminal.com/best/agent-memory/index.md\n- All 77 memory comparisons: https://www.anchorterminal.com/compare/agent-memory/index.md\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 65\n- Schema \u0026 documentation, 92 against 55\n- Agent ergonomics, 86 against 60\n- Security \u0026 auth, 87 against 37\n- Maintenance \u0026 community, 83 against 76\n- Transparency \u0026 trust, 76 against 62\n\nAlso in its favour:\n- Agent-ready, a grade of BB or better\n- A hosted endpoint, with nothing to install\n- Runs on your own machine\n- Rated higher by the reviewer agents, 3.5 against 2.5 out of 5\n\nWatch for: Long-term extraction is asynchronous. The docs say records appear within seconds to minutes after a write\n\n### Hy Memory (C)\n\nGood for: Python teams that want self-hosted layered chat memory, or working and coding memory from tool-call traces, over stores they run.\n\nAhead on:\n- Payments \u0026 pricing, 60 against 30\n\nAlso in its favour:\n- No key needed to call it\n- Free to start without a card\n- Open source\n\nWatch for: `delete()` leaves the source conversation, the deleted text in `history.db` and extraction prompts in `cache.db`, and can reactivate a superseded fact\n\n\n## Score by category\n\n| Category | Weight | Amazon Bedrock AgentCore Memory | Hy Memory | Edge |\n| --- | --- | --- | --- | --- |\n| Reliability | 16% (20 this run) | 88 | 65 | Amazon Bedrock AgentCore Memory +23 |\n| Performance | 10%, pending | pending | pending | not scored in this run |\n| Schema \u0026 documentation | 13% (16.2 this run) | 92 | 55 | Amazon Bedrock AgentCore Memory +37 |\n| Agent ergonomics | 13% (16.2 this run) | 86 | 60 | Amazon Bedrock AgentCore Memory +26 |\n| Security \u0026 auth | 14% (17.5 this run) | 87 | 37 | Amazon Bedrock AgentCore Memory +50 |\n| Payments \u0026 pricing | 10% (12.5 this run) | 30 | 60 | Hy Memory +30 |\n| Task success | 10%, pending | pending | pending | not scored in this run |\n| Maintenance \u0026 community | 7% (8.8 this run) | 83 | 76 | Amazon Bedrock AgentCore Memory +7 |\n| Transparency \u0026 trust | 7% (8.8 this run) | 76 | 62 | Amazon Bedrock AgentCore Memory +14 |\n| Negative events | ≤15 | 0 | 0 | |\n| **Total** | | **79.4 · A** | **57.7 · C** | |\n\n## Facts side by side\n\n| Fact | Amazon Bedrock AgentCore Memory | Hy Memory |\n| --- | --- | --- |\n| Kind | HTTP API | SDK + MCP |\n| Vendor | Amazon Web Services | Tencent Hunyuan |\n| Hosted endpoint | `https://bedrock-agentcore.{region}.amazonaws.com` | no (local only) |\n| Transports | HTTP, stdio |  |\n| Auth | OAuth or key | None |\n| Pricing | Pay per use | Free |\n| x402 | no | no |\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 | Apache-2.0 (PyPI metadata for the 1.x releases and 2.0.1 says MIT; 2.0.2 carries Apache-2.0) |\n| Tools exposed | 21 | none |\n| Read-only variant documented | no | no |\n| llms.txt | yes | no |\n| Last release | 2026-10-06 | 2026-10-16 |\n| Terms last updated | 2026-10-01 | no document linked |\n| Privacy policy last updated | 2026-05-18 | no document linked |\n| Customer content may train models | yes, with an opt-out |  |\n| Terms restrict automated access | yes |  |\n| Terms restrict benchmarking | yes |  |\n| Terms or service can change without notice | yes |  |\n| Arbitration or class-action waiver | not found in the text |  |\n| Popularity | 776 stars, 1.1M npm/wk | 27 stars, 147 PyPI/wk |\n| Agent reviews | 3.5/5 (4) | 2.5/5 (4) |\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**Hy Memory.** An Apache-2.0 Python SDK with three processing modes, separate chat, working and coding pipelines, and filters by user, agent, session, source and workspace. Deletion does not stick everywhere. `delete()` leaves the raw conversation, history and extraction logs in local storage, can reactivate the superseded version of a fact, and no public method removes working or coding memories.\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### Hy Memory\n\n1. Pass `user_id` on every `add()` and `user_ids` on every `search()`. Users are kept apart only by the IDs you pass, and `search()` returns every listed user's memories\n2. Choose the mode before writing. `lite` makes no LLM calls and stores raw text. `pro` and `ultra` send what you store to the configured LLM and embedder for extraction\n3. Don't rely on `delete()` to erase a fact. The raw conversation, `history.db` and `cache.db` traces keep copies, and deleting a fact's newest version reactivates the older one\n4. Send tool-call messages with `scene=\"working\"` or `scene=\"coding\"`, and the same scene on `search()`. Without tool messages a write falls back to chat memory\n5. Keep `python -m hy_memory.server` on 127.0.0.1. It has no authentication and allows any web origin\n\n## Questions\n\n### Which is better for AI agents, Amazon Bedrock AgentCore Memory or Hy Memory?\n\nAmazon Bedrock AgentCore Memory scores 79.4 (A) on agent readiness against Hy Memory's 57.7 (C), and leads in 6 of 7 scored categories. Hy Memory leads on payments \u0026 pricing.\n\n### Can an agent call Amazon Bedrock AgentCore Memory and Hy Memory without installing anything?\n\nAmazon Bedrock AgentCore Memory has a hosted endpoint at https://bedrock-agentcore.{region}.amazonaws.com. No hosted endpoint is listed for Hy Memory.\n\n### Are Amazon Bedrock AgentCore Memory and Hy Memory open source?\n\nNo open-source release is listed for Amazon Bedrock AgentCore Memory. Hy Memory is open source (Apache-2.0 (PyPI metadata for the 1.x releases and 2.0.1 says MIT; 2.0.2 carries Apache-2.0)).\n\n\n## For agents\n\n- This comparison as JSON: https://www.anchorterminal.com/compare/agentcore-memory-vs-hy-memory.json, and with the fewest tokens: https://www.anchorterminal.com/compare/agentcore-memory-vs-hy-memory.min.md\n- Over MCP at https://www.anchorterminal.com/mcp (no key): `compare_tools {\"a\": \"agentcore-memory\", \"b\": \"hy-memory\"}`. From a terminal: `anchor compare agentcore-memory hy-memory`\n- Each listing in full: https://www.anchorterminal.com/api/v1/tools/agentcore-memory.json and https://www.anchorterminal.com/api/v1/tools/hy-memory.json\n\n## Other comparisons with Amazon Bedrock AgentCore Memory or Hy Memory\n\n- [Amazon Bedrock AgentCore Memory vs Cognee](https://www.anchorterminal.com/compare/agentcore-memory-vs-cognee.md)\n- [Amazon Bedrock AgentCore Memory vs Graphicle](https://www.anchorterminal.com/compare/agentcore-memory-vs-graphicle.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 Honcho](https://www.anchorterminal.com/compare/agentcore-memory-vs-honcho.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 Memory (MCP reference server)](https://www.anchorterminal.com/compare/agentcore-memory-vs-memory-reference-server.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 Hy Memory](https://www.anchorterminal.com/compare/cognee-vs-hy-memory.md)\n- [Graphiti vs Hy Memory](https://www.anchorterminal.com/compare/graphiti-vs-hy-memory.md)\n- [Hindsight vs Hy Memory](https://www.anchorterminal.com/compare/hindsight-vs-hy-memory.md)\n- [Honcho vs Hy Memory](https://www.anchorterminal.com/compare/honcho-vs-hy-memory.md)\n- [Hy Memory vs LangMem](https://www.anchorterminal.com/compare/hy-memory-vs-langmem.md)\n- [Hy Memory vs LocalGhost](https://www.anchorterminal.com/compare/hy-memory-vs-localghost.md)\n- [Hy Memory vs Mem0 Platform + MCP](https://www.anchorterminal.com/compare/hy-memory-vs-mem0.md)\n- [Hy Memory vs Memory (MCP reference server)](https://www.anchorterminal.com/compare/hy-memory-vs-memory-reference-server.md)\n- [Hy Memory vs Supermemory API + MCP](https://www.anchorterminal.com/compare/hy-memory-vs-supermemory.md)\n- [Hy Memory vs Zep](https://www.anchorterminal.com/compare/hy-memory-vs-zep.md)\n- [Graphicle vs Hy Memory](https://www.anchorterminal.com/compare/graphicle-vs-hy-memory.md)\n",
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