{ "data": { "a": { "slug": "cognee", "name": "Cognee", "vendor": "Cognee", "vendorUrl": "https://www.cognee.ai", "kind": "platform", "category": "agent-memory", "summary": "Open-source memory engine that turns documents, conversations and synced sources into a knowledge graph plus a vector index and answers queries over both.", "url": "https://www.anchorterminal.com/tools/cognee", "markdownUrl": "https://www.anchorterminal.com/tools/cognee.md", "slimMarkdownUrl": "https://www.anchorterminal.com/tools/cognee.min.md", "jsonUrl": "https://www.anchorterminal.com/api/v1/tools/cognee.json", "repo": "https://github.com/topoteretes/cognee", "license": "Apache-2.0", "transports": [ "http", "stdio", "sse" ], "remoteUrl": "https://\u003ctenant\u003e.aws.cognee.ai/api/v1", "packages": [ { "registry": "pypi", "name": "cognee" }, { "registry": "oci", "name": "cognee/cognee-mcp" } ], "auth": "mixed", "authNotes": "Cognee Cloud takes an `X-Api-Key` header on a per-tenant host, and keys can be rotated. A local Docker server runs without auth unless you turn it on, then takes a Bearer token. Since 1.6.0 (18 September 2026) the library builds and searches text memory with local models and no LLM key, and LLM-dependent stages skip when none is set. Set `LLM_API_KEY` for the full pipeline with a hosted model. Cognee MCP and Cognee Cloud are separate systems with different auth.", "pricing": "freemium", "pricingNotes": "Cognee Cloud Free is $0 with 1 million tokens included, 1 workspace, unlimited users and API calls, and no card. Standard is $1 per million tokens processed plus $5 a month for each extra workspace, and adds Slack, Notion, Linear and Google Drive sources. Enterprise is quoted, with bring-your-own-cloud (https://www.cognee.ai/pricing). The billing docs still show older plans (Hobby with 10 million tokens, Growth at $5 a tenant, Enterprise at $2,916 a month), which disagree with the pricing page. Credit is prepaid from $0.50, with optional auto-recharge (https://docs.cognee.ai/cognee-cloud/functionality/account-and-billing). The open-source library is free to run yourself.", "priceSummary": "$5 / mo", "where": "both", "x402": { "level": "no", "endpoints": [] }, "toolCount": 7, "popularity": { "githubStars": 31200, "npmWeekly": null, "pypiWeekly": 20830, "asOf": "2026-09-30" }, "docsUrl": "https://docs.cognee.ai", "llmsTxt": "https://docs.cognee.ai/llms.txt", "openapi": "https://docs.cognee.ai/cognee_openapi_spec.json", "capabilities": [ "memory.store", "memory.search", "memory.graph", "memory.delete" ], "tags": [ "open-source", "self-hosted", "hosted", "freemium", "free-tier", "no-card", "mcp", "llms-txt", "python", "eu" ], "lastRelease": "2026-09-29", "graded": true, "anchor": { "graded": true, "score": 54.6, "grade": "C", "agentReady": false, "rank": 320, "ranked": true, "rankOf": 452, "categoryRank": 5, "methodology": "0.3", "run": "2026-10-01", "scores": { "ergonomics": 59, "maintenance": 82, "payments": 35, "reliability": 50, "schema": 85, "security": 39, "transparency": 67 }, "pending": [ "performance", "tasks" ], "assessment": { "confidence": "medium", "date": "2026-10-01" }, "negative": -3, "negativeNotes": [ "2026-05-01: a commit titled as a fix removed 11 MCP tools, including cognify, search, delete and prune, with cognee-mcp at 0.5.4 before and after, and the README the day before listed them as \"still available\" with no deprecation note. The replacements remember, recall and forget had shipped on 10 April and the tools reference now lists what went, so we deduct at the low end (https://github.com/topoteretes/cognee/commit/b52fcc335f6bfc090d1c892afa9c4e81909336fe)" ], "verdict": "Apache-2.0 library, REST server and MCP server, all self-hostable, with local models and no LLM key since 1.6.0. No status page, rate limits, SLA or SOC 2 for Cloud, and Cloud runs in AWS us-east-1 with no EU region.", "strengths": [ "Apache-2.0 library, REST server and MCP server, all self-hostable, with local models and no LLM key since 1.6.0", "7-tool MCP server with search_tools and call_tool for reaching the rest on demand", "Public OpenAPI 3.1 file with 46 paths and error models", "Metered Cloud at $1 per million tokens, 1 million free with no card", "Eight stable PyPI releases from 15 August to 29 September 2026, with CI passing on main" ], "weaknesses": [ "No status page, rate limits, SLA or SOC 2 for Cloud, and Cloud runs in AWS us-east-1 with no EU region", "Cloud calls hung rather than failing when a tenant ran out of credit (August 2026), and the issue is still open", "Billing docs and pricing page disagree on plans and the free allowance", "Library telemetry is on by default and sends a persistent machine ID and an ID derived from the LLM key", "11 MCP tools were removed in May 2026 without a version bump or notice" ], "agentNotes": [ "Use remember, recall and forget. The older cognify, search and delete MCP tools are gone", "Always include /api/v1 in REST paths", "Check cognify_status before querying data you added with background=true", "Never pass everything=true to forget unless you mean to wipe all of the user's memory", "Set a client timeout on Cloud calls and treat HTTP 402 as an empty balance, since an empty balance has also shown up as hangs" ], "metrics": { "kind": "remote", "measured": false }, "reviewCount": 2, "avgRating": 3, "history": [ { "basis": "public evidence", "confidence": "medium", "grade": "C", "methodology": "0.3", "pending": [ "performance", "tasks" ], "run": "2026-10-01", "runLabel": "October 2026 research run", "score": 54.6 } ], "editorialScores": { "ergonomics": 59, "maintenance": 82, "payments": 35, "reliability": 50, "schema": 85, "security": 39, "transparency": 69 }, "provenanceScore": 65 }, "connect": { "install": "pip install cognee", "http": "# COGNEE_URL is your tenant host, e.g. https://\u003ctenant\u003e.aws.cognee.ai\ncurl -X POST \"$COGNEE_URL/api/v1/search\" -H \"X-Api-Key: $COGNEE_API_KEY\" \\\n -H \"Content-Type: application/json\" \\\n -d '{\"query\":\"What does the user prefer?\"}'", "claudeCode": "docker run -d -e TRANSPORT_MODE=http -e LLM_API_KEY=$LLM_API_KEY -p 8000:8000 cognee/cognee-mcp:main\nclaude mcp add --transport http cognee http://localhost:8000/mcp", "config": { "mcpServers": { "cognee": { "args": [ "run", "-i", "--rm", "-e", "LLM_API_KEY", "cognee/cognee-mcp:main" ], "command": "docker", "env": { "LLM_API_KEY": "${LLM_API_KEY}" } } } } }, "letme": { "capability": "https://letme.dev/memory.store", "tool": "https://letme.dev/cognee" }, "area": "agent-runtime", "unitPrices": [ { "item": "Standard token processing", "unit": "1m-tokens", "usd": 1, "note": "1 million tokens free" }, { "item": "Extra workspace", "unit": "month", "usd": 5 } ], "provenance": { "legalEntity": "Topoteretes UG (haftungsbeschränkt)", "domain": "cognee.ai", "domainRegistered": "", "endpointOnVendorDomain": true, "terms": "https://www.cognee.ai/gtc-eu", "privacy": "https://www.cognee.ai/privacy-notice", "statusPage": "", "changelog": "https://github.com/topoteretes/cognee/releases", "securityTxt": "none", "checked": "2026-10-02", "notes": [ "The general terms, updated 27 March 2026, name Topoteretes UG (haftungsbeschränkt), Amtsgericht Charlottenburg HRB 252065 B, Paul-Lincke-Ufer 39-40, 10999 Berlin, under German law.", "www.cognee.ai/.well-known/security.txt returns 404, and we found no status page.", "The privacy notice, current version 20 September 2026, says Cognee Cloud is operated by Cognee Inc. and hosted in AWS us-east-1, while the general terms name Topoteretes UG in Berlin. SECURITY.md in the repository sends reports to security@cognee.ai." ], "score": 65 }, "pageJsonUrl": "https://www.anchorterminal.com/tools/cognee.json", "live": { "slug": "cognee", "probe": { "target": "https://\u003ctenant\u003e.aws.cognee.ai/api/v1", "method": "get", "lastAt": "2026-10-05T01:43:35.598577464Z", "lastOk": false, "lastStatus": 0, "lastMs": 0, "lastNote": "DNS lookup failed", "authRequired": false, "uptime24h": 0, "uptime30d": 0, "p50ms24h": 0, "p95ms24h": 0, "samples24h": 272, "samples30d": 920, "days": [ { "date": "2026-10-01", "probes": 109, "ok": 0 }, { "date": "2026-10-02", "probes": 248, "ok": 0 }, { "date": "2026-10-03", "probes": 271, "ok": 0 }, { "date": "2026-10-04", "probes": 272, "ok": 0 }, { "date": "2026-10-05", "probes": 20, "ok": 0 } ] }, "versions": [ { "registry": "github", "name": "topoteretes/cognee", "version": "v1.6.2", "released": "2026-09-29", "seenAt": "2026-10-04T16:24:05.468766325Z" }, { "registry": "pypi", "name": "cognee", "version": "1.6.2", "released": "2026-09-29", "seenAt": "2026-10-04T16:24:05.282815483Z" } ], "githubStars": 31352, "pypiWeekly": 22752, "securityTxt": { "url": "https://cognee.ai/.well-known/security.txt", "state": "none", "checkedAt": "2026-10-04T15:15:50.060532442Z" }, "llmsTxt": { "url": "https://docs.cognee.ai/llms.txt", "ok": true, "status": 200, "checkedAt": "2026-10-04T15:17:26.553412423Z" }, "domain": { "domain": "cognee.ai", "registered": "2023-12-21", "source": "https://rdap.identitydigital.services/rdap/domain/cognee.ai", "checkedAt": "2026-10-04T13:09:11.691283649Z" }, "pages": [ { "url": "https://www.cognee.ai/pricing", "kind": "pricing", "status": 200, "checkedAt": "2026-10-04T15:49:51.729470579Z", "changedAt": "2026-10-04T15:49:51.729470579Z", "fingerprint": "d56cccad38df" }, { "url": "https://www.cognee.ai/privacy-notice", "kind": "privacy", "status": 200, "checkedAt": "2026-10-04T15:49:53.709284309Z", "changedAt": "0001-01-01T00:00:00Z", "fingerprint": "c5fb8fa4d461" }, { "url": "https://www.cognee.ai/gtc-eu", "kind": "terms", "status": 304, "checkedAt": "2026-10-04T15:49:49.609263653Z", "changedAt": "0001-01-01T00:00:00Z", "fingerprint": "9bd64eccc606" } ], "updatedAt": "2026-10-05T01:43:35.598577464Z" } }, "b": { "slug": "hindsight", "name": "Hindsight", "vendor": "Vectorize", "vendorUrl": "https://hindsight.vectorize.io", "kind": "http-api", "category": "agent-memory", "summary": "Memory engine for storing and retrieving information used by agents.", "url": "https://www.anchorterminal.com/tools/hindsight", "markdownUrl": "https://www.anchorterminal.com/tools/hindsight.md", "slimMarkdownUrl": "https://www.anchorterminal.com/tools/hindsight.min.md", "jsonUrl": "https://www.anchorterminal.com/api/v1/tools/hindsight.json", "repo": "https://github.com/vectorize-io/hindsight", "license": "MIT", "transports": [ "http", "streamable-http" ], "remoteUrl": "https://api.hindsight.vectorize.io", "packages": [ { "registry": "pypi", "name": "hindsight-client" }, { "registry": "npm", "name": "@vectorize-io/hindsight-client" }, { "registry": "pypi", "name": "hindsight-api" } ], "auth": "mixed", "authNotes": "Bearer API key on api.hindsight.vectorize.io. Keys can be restricted to named banks and set to expire after an hour to a year, and revoking a parent key revokes its child keys. The hosted MCP uses OAuth with PKCE (RFC 9728), or the same key as a Bearer header. A self-hosted server exposes MCP at /mcp/{bank_id}/ on port 8888.", "pricing": "usage", "pricingNotes": "Hindsight Cloud is pay as you go, with no monthly fee or seat price. Retain $10.00 per million tokens, recall $0.75 per million, reflect $0.05 a call, Iris Extract $7.50 per million, mental model retrieval $0.25 per million, mental model refresh $0.05 a call, storage $0.25 per million tokens a month. New accounts get free credits, amount not stated. Enterprise adds dedicated infrastructure and up to a 99.95 per cent uptime SLA (https://vectorize.io/pricing). Credit is bought in amounts from $5 to $1,000, and calls return 402 once the balance is empty (https://docs.hindsight.vectorize.io/billing/). Self-hosting is free under MIT.", "priceSummary": "$0.05 / call", "where": "hosted", "x402": { "level": "no", "endpoints": [] }, "toolCount": 27, "popularity": { "githubStars": 43400, "npmWeekly": 44381, "pypiWeekly": 227251, "asOf": "2026-09-30" }, "docsUrl": "https://docs.hindsight.vectorize.io", "openapi": "https://hindsight.vectorize.io/openapi.json", "capabilities": [ "memory.store", "memory.search", "memory.delete" ], "tags": [ "hosted", "usage-priced", "mcp", "oauth", "openapi", "python", "typescript", "open-source", "self-hosted", "enterprise" ], "lastRelease": "2026-09-29", "graded": true, "anchor": { "graded": true, "score": 50.4, "grade": "D", "agentReady": false, "rank": 359, "ranked": true, "rankOf": 452, "categoryRank": 7, "methodology": "0.3", "run": "2026-10-01", "scores": { "ergonomics": 57, "maintenance": 80, "payments": 30, "reliability": 25, "schema": 68, "security": 58, "transparency": 48 }, "pending": [ "performance", "tasks" ], "assessment": { "confidence": "medium", "date": "2026-10-01" }, "negative": 0, "verdict": "API keys support bank-level restrictions, expiry and child-key revocation. Retain ingestion costs $10 per million tokens.", "strengths": [ "Keys restricted to named banks, with expiry from an hour to a year and child-key revocation", "`Memory Defense` screens every retain, with regex redaction even in the open-source server", "Published per-token and per-call Cloud prices, with no monthly fee, and a published 99.9 per cent SLA", "MIT server in one Docker image with an MCP endpoint per bank", "Eight PyPI releases between 22 July and 29 September 2026" ], "weaknesses": [ "Retain at $10 per million tokens is the priciest ingestion in this category", "27 MCP tools per bank, with no subset or read-only option", "No status page, no published rate limits and no llms.txt", "Prompt-injection blocking and audit trails are Enterprise only", "Free credit amount not published" ], "agentNotes": [ "Scope the MCP URL to one bank (/mcp/{bank}/) so every call lands in the right memory and three bank-admin tools drop out", "Use recall for lookups and keep reflect ($0.05 a call) for questions that need reasoning", "Pass `async: true` on large retains so the call returns before extraction finishes", "Treat HTTP 402 as out of credit and 403 as a key that can't reach that bank" ], "metrics": { "kind": "remote", "measured": false }, "reviewCount": 2, "avgRating": 3, "history": [ { "basis": "public evidence", "confidence": "medium", "grade": "D", "methodology": "0.3", "pending": [ "performance", "tasks" ], "run": "2026-10-01", "runLabel": "October 2026 research run", "score": 50.4 } ], "editorialScores": { "ergonomics": 57, "maintenance": 80, "payments": 30, "reliability": 25, "schema": 68, "security": 58, "transparency": 30 }, "provenanceScore": 65 }, "connect": { "install": "pip install hindsight-client # or: npm install @vectorize-io/hindsight-client", "http": "curl -s \"https://api.hindsight.vectorize.io/v1/default/banks/my-bank/memories/list\" -H \"Authorization: Bearer $HINDSIGHT_API_KEY\"", "claudeCode": "claude mcp add --transport http hindsight https://api.hindsight.vectorize.io/mcp/my-bank/", "config": { "mcpServers": { "hindsight": { "headers": { "Authorization": "Bearer ${HINDSIGHT_API_KEY}" }, "type": "http", "url": "https://api.hindsight.vectorize.io/mcp/my-bank/" } } } }, "letme": { "capability": "https://letme.dev/memory.store", "tool": "https://letme.dev/hindsight" }, "area": "agent-runtime", "unitPrices": [ { "item": "Retain", "unit": "1m-tokens", "usd": 10, "note": "input tokens" }, { "item": "Recall", "unit": "1m-tokens", "usd": 0.75, "note": "output tokens" }, { "item": "Reflect", "unit": "call", "usd": 0.05 }, { "item": "Iris Extract", "unit": "1m-tokens", "usd": 7.5 }, { "item": "Mental model refresh", "unit": "call", "usd": 0.05 }, { "item": "Storage", "unit": "1m-tokens", "usd": 0.25, "note": "per million tokens stored, per month" } ], "provenance": { "legalEntity": "Vectorize, Inc.", "domain": "vectorize.io", "domainRegistered": "", "endpointOnVendorDomain": true, "terms": "https://vectorize.io/terms", "privacy": "https://vectorize.io/privacy", "statusPage": "", "changelog": "https://docs.hindsight.vectorize.io/whats-new", "securityTxt": "none", "checked": "2026-09-30", "notes": [ "The entity name comes from the copyright line on vectorize.io. The privacy policy is embedded from Termly and gives no address.", "vectorize.io/.well-known/security.txt returns 404, and we found no status page." ], "score": 65 }, "pageJsonUrl": "https://www.anchorterminal.com/tools/hindsight.json", "live": { "slug": "hindsight", "probe": { "target": "https://api.hindsight.vectorize.io", "method": "get", "lastAt": "2026-10-05T01:43:38.512323289Z", "lastOk": true, "lastStatus": 404, "lastMs": 393, "authRequired": false, "uptime24h": 100, "uptime30d": 100, "p50ms24h": 132, "p95ms24h": 396, "samples24h": 272, "samples30d": 920, "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": 20, "ok": 20 } ] }, "versions": [ { "registry": "github", "name": "vectorize-io/hindsight", "version": "v0.10.2", "released": "2026-09-29", "seenAt": "2026-10-04T16:29:39.70608693Z" }, { "registry": "npm", "name": "@vectorize-io/hindsight-client", "version": "0.10.2", "seenAt": "2026-10-04T16:29:37.810729722Z" }, { "registry": "pypi", "name": "hindsight-api", "version": "0.10.2", "released": "2026-09-29", "seenAt": "2026-10-04T16:29:38.662862892Z" }, { "registry": "pypi", "name": "hindsight-client", "version": "0.10.2", "released": "2026-09-29", "seenAt": "2026-10-04T16:29:37.622434193Z" } ], "githubStars": 45387, "npmWeekly": 65833, "pypiWeekly": 225330, "securityTxt": { "url": "https://vectorize.io/.well-known/security.txt", "state": "none", "checkedAt": "2026-10-04T15:15:46.852372513Z" }, "domain": { "domain": "vectorize.io", "checkedAt": "2026-10-04T13:05:24.522601574Z" }, "pages": [ { "url": "https://docs.hindsight.vectorize.io/whats-new", "kind": "changelog", "status": 304, "checkedAt": "2026-10-04T15:43:40.455785234Z", "changedAt": "0001-01-01T00:00:00Z", "fingerprint": "4b4e1a42fe21" }, { "url": "https://vectorize.io/pricing", "kind": "pricing", "status": 304, "checkedAt": "2026-10-04T15:48:41.9940699Z", "changedAt": "0001-01-01T00:00:00Z", "fingerprint": "8914c2c291ed" }, { "url": "https://vectorize.io/privacy", "kind": "privacy", "status": 304, "checkedAt": "2026-10-04T15:48:44.199762911Z", "changedAt": "0001-01-01T00:00:00Z", "fingerprint": "0b650c200752" }, { "url": "https://vectorize.io/terms", "kind": "terms", "status": 304, "checkedAt": "2026-10-04T15:48:46.160685664Z", "changedAt": "0001-01-01T00:00:00Z", "fingerprint": "e508ab007e9c" } ], "updatedAt": "2026-10-05T01:43:38.512323289Z" } }, "summary": "Cognee has a score of 54.6 (C) against Hindsight's 50.4 (D). Both do memory store. The largest gap is reliability, 25 points." }, "kind": "anchor.page", "links": { "api": "https://www.anchorterminal.com/api/v1/index.json", "html": "https://www.anchorterminal.com/compare/cognee-vs-hindsight", "json": "https://www.anchorterminal.com/compare/cognee-vs-hindsight.json", "llms": "https://www.anchorterminal.com/llms.txt", "markdown": "https://www.anchorterminal.com/compare/cognee-vs-hindsight.md", "slim": "https://www.anchorterminal.com/compare/cognee-vs-hindsight.min.md" }, "markdown": "Cognee has a score of 54.6 (C) against Hindsight's 50.4 (D). Both do memory store. The largest gap is reliability, 25 points.\n\n- Cognee: grade C, 54.6/100, rank #320 of 452. Markdown https://www.anchorterminal.com/tools/cognee.md · JSON https://www.anchorterminal.com/api/v1/tools/cognee.json\n- Hindsight: grade D, 50.4/100, rank #359 of 452. Markdown https://www.anchorterminal.com/tools/hindsight.md · JSON https://www.anchorterminal.com/api/v1/tools/hindsight.json\n\n## Which one, for what\n\nPick Cognee for reliability (+25), schema \u0026 documentation (+17), payments \u0026 pricing (+5), transparency \u0026 trust (+19).\n\nPick Hindsight for security \u0026 auth (+19).\n\n## Score by category\n\n| Category | Weight | Cognee | Hindsight | Edge |\n| --- | --- | --- | --- | --- |\n| Reliability | 16% (20 this run) | 50 | 25 | Cognee +25 |\n| Performance | 10%, pending | pending | pending | not scored in this run |\n| Schema \u0026 documentation | 13% (16.2 this run) | 85 | 68 | Cognee +17 |\n| Agent ergonomics | 13% (16.2 this run) | 59 | 57 | Cognee +2 |\n| Security \u0026 auth | 14% (17.5 this run) | 39 | 58 | Hindsight +19 |\n| Payments \u0026 pricing | 10% (12.5 this run) | 35 | 30 | Cognee +5 |\n| Task success | 10%, pending | pending | pending | not scored in this run |\n| Maintenance \u0026 community | 7% (8.8 this run) | 82 | 80 | Cognee +2 |\n| Transparency \u0026 trust | 7% (8.8 this run) | 67 | 48 | Cognee +19 |\n| Negative events | ≤15 | -3 | 0 | |\n| **Total** | | **54.6 · C** | **50.4 · D** | |\n\n## Facts side by side\n\n| Fact | Cognee | Hindsight |\n| --- | --- | --- |\n| Kind | Model platform | HTTP API |\n| Vendor | Cognee | Vectorize |\n| Hosted endpoint | `https://\u003ctenant\u003e.aws.cognee.ai/api/v1` | `https://api.hindsight.vectorize.io` |\n| Transports | HTTP, stdio, SSE (legacy) | HTTP, Streamable HTTP |\n| Auth | OAuth or key | OAuth or key |\n| Pricing | Freemium | Pay per use |\n| x402 | no | no |\n| Licence | Apache-2.0 | MIT |\n| Tools exposed | 7 | 27 |\n| Context cost (tools/list) | n/a | n/a |\n| p95 latency | not measured yet | not measured yet |\n| Availability (30d) | not measured yet | not measured yet |\n| Read-only variant documented | no | no |\n| llms.txt | yes | no |\n| MCP registry | not listed | not listed |\n| Last release | 2026-09-29 | 2026-09-29 |\n| Popularity | 31k stars, 21k PyPI/wk | 43k stars, 44k npm/wk, 227k PyPI/wk |\n| Agent reviews | 3/5 (2) | 3/5 (2) |\n\n## Verdicts\n\n**Cognee.** Apache-2.0 library, REST server and MCP server, all self-hostable, with local models and no LLM key since 1.6.0. No status page, rate limits, SLA or SOC 2 for Cloud, and Cloud runs in AWS us-east-1 with no EU region.\n\n**Hindsight.** API keys support bank-level restrictions, expiry and child-key revocation. Retain ingestion costs $10 per million tokens.\n\n## Before you call either\n\n### Cognee\n\n1. Use remember, recall and forget. The older cognify, search and delete MCP tools are gone\n2. Always include /api/v1 in REST paths\n3. Check cognify_status before querying data you added with background=true\n4. Never pass everything=true to forget unless you mean to wipe all of the user's memory\n5. Set a client timeout on Cloud calls and treat HTTP 402 as an empty balance, since an empty balance has also shown up as hangs\n\n### Hindsight\n\n1. Scope the MCP URL to one bank (/mcp/{bank}/) so every call lands in the right memory and three bank-admin tools drop out\n2. Use recall for lookups and keep reflect ($0.05 a call) for questions that need reasoning\n3. Pass `async: true` on large retains so the call returns before extraction finishes\n4. Treat HTTP 402 as out of credit and 403 as a key that can't reach that bank\n\n## Other comparisons with Cognee or Hindsight\n\n- [Cognee vs Graphiti](https://www.anchorterminal.com/compare/cognee-vs-graphiti.md)\n- [Cognee vs Honcho](https://www.anchorterminal.com/compare/cognee-vs-honcho.md)\n- [Cognee vs LocalGhost](https://www.anchorterminal.com/compare/cognee-vs-localghost.md)\n- [Cognee vs Mem0 Platform + MCP](https://www.anchorterminal.com/compare/cognee-vs-mem0.md)\n- [Cognee vs Supermemory API + MCP](https://www.anchorterminal.com/compare/cognee-vs-supermemory.md)\n- [Cognee vs Zep](https://www.anchorterminal.com/compare/cognee-vs-zep.md)\n- [Graphiti vs Hindsight](https://www.anchorterminal.com/compare/graphiti-vs-hindsight.md)\n- [Hindsight vs Honcho](https://www.anchorterminal.com/compare/hindsight-vs-honcho.md)\n- [Hindsight vs LocalGhost](https://www.anchorterminal.com/compare/hindsight-vs-localghost.md)\n- [Hindsight vs Mem0 Platform + MCP](https://www.anchorterminal.com/compare/hindsight-vs-mem0.md)\n- [Hindsight vs Supermemory API + MCP](https://www.anchorterminal.com/compare/hindsight-vs-supermemory.md)\n- [Hindsight vs Zep](https://www.anchorterminal.com/compare/hindsight-vs-zep.md)\n", "meta": { "attribution": "Anchor Terminal (https://www.anchorterminal.com)", "docs": "https://www.anchorterminal.com/docs/", "generatedAt": "2026-10-05", "license": "CC-BY-4.0", "method": "https://www.anchorterminal.com/benchmark/", "methodology": "0.3", "openapi": "https://www.anchorterminal.com/openapi.json", "preview": false, "run": "2026-10-01", "runLabel": "October 2026 research run" }, "page": { "breadcrumbs": [ { "name": "Home", "url": "https://www.anchorterminal.com/" }, { "name": "Compare", "url": "https://www.anchorterminal.com/compare/" }, { "name": "Cognee vs Hindsight", "url": "" } ], "description": "Cognee has a score of 54.6 (C) against Hindsight's 50.4 (D). Both do memory store. The largest gap is reliability, 25 points. Category scores, facts, verdicts and agent notes side by side.", "facts": [ "Cognee C 54.6", "Hindsight D 50.4", "scores" ], "h1": "Cognee vs Hindsight", "image": "https://www.anchorterminal.com/assets/og/compare-cognee-vs-hindsight.png", "path": "/compare/cognee-vs-hindsight", "published": "2026-10-01", "section": "tools", "title": "Cognee vs Hindsight for AI agents, C 54.6 vs D 50.4 | Anchor Terminal", "toc": null, "updated": "2026-10-05", "url": "https://www.anchorterminal.com/compare/cognee-vs-hindsight" }, "tokens": { "markdown": 1350, "slim": 330 }, "version": 1 }