Document QA Agent
Query this niche via MCP
market_report({ query: "Document QA Agent", response_mode: "summary" })Agents · median
$16/mo
MCP servers · median
All plans — Agents vs MCPs
each dot = one provider · log scaleAgents $16
ekstrakt · $6
smry · $6
skipit · $13
Boei Pdf Ai · $19
Hyperwrite Text Extractor · $29
1min Ai Pdf Chat · $7
aiagentdocs · $13
pdfpeer · $15
Hyperwrite Text Extractor · $16
Google Drive Rag Agent · $29
Ai Drive · $39
smry · $80
1min Ai Pdf Chat · $10
Boei Pdf Ai · $129
Ai Drive · $200
$5
$10
$25
$50
$100
AgentsMCP serversshaded = middle half · line = median
All plans
15 pricedProvidervs its cohort medianMonthly
ekstraktagent
$6 below
smryagent
$6 below
1min Ai Pdf Chatagent
$7 below
1min Ai Pdf Chatagent
$10 below
skipitagent
$13 below
aiagentdocsagent
$13 below
pdfpeeragent
$15 ~median
Hyperwrite Text Extractoragent
$16 ~median
Boei Pdf Aiagent
$19 above
Hyperwrite Text Extractoragent
$29 above
Google Drive Rag Agentagent
$29 above
Ai Driveagent
$39 above
smryagent
$80 above
Boei Pdf Aiagent
$129 above
Ai Driveagent
$200 above
Position is relative to the provider's own delivery-type median at this tier — never a blended one.
What the figures on this page are. This page is Agentery's fixed-niche view of Document QA Agent (latest observation 2026-10-15T03:43:03.005Z). The headline medians above are computed from that data per delivery type and buyer-tier tab: on a tier tab, the median of each provider's plan at that tier; on “All”, every priced plan point across tiers pooled. Small cohorts show as “too few” rather than a median. The embedded response below is the broader fixed-niche report: its
by_provider_type.*.median pools all tiers, pricing.byPersona.* is per buyer tier, and the unit cohorts (e.g. Pro flat) are per tier and billing unit — so those blocks legitimately differ from one headline figure. Over MCP today the advertised tools are market_report (a semantic neighbourhood for your query, not this fixed niche) and price_benchmark (query/task); niche_report stays callable as a legacy alias. Their cohorts are defined differently, so their numbers can differ from this page.market_reportprice_benchmark
See the MCP response behind this pagefixed-niche report (legacy niche_report alias, full mode) — broader than the headline figure
{
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"billingMix": {
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"usage": 3,
"subscription": 4,
"free": 8
},
"freeTierShare": 0.67,
"medianLowestUsd": 12.99
},
"movement": {
"niche": "document-qa-agent",
"sector": "research-knowledge-work",
"pricedNow": 9,
"pairs": 8,
"repriced": [],
"newlyPriced": [
"1min_ai_pdf_chat"
],
"droppedFromPriced": [],
"likeForLikePct": 0,
"kind": "composition",
"narrative": "Composition change (average moved, but no agent changed its price): 1 newly published pricing."
},
"index_series": {
"series": [
{
"day": "2026-09-15",
"index": 100,
"pairs": 15,
"dayChangePct": 0
},
{
"day": "2026-09-16",
"index": 100,
"pairs": 15,
"dayChangePct": 0
},
{
"day": "2026-09-17",
"index": 100,
"pairs": 14,
"dayChangePct": 0
},
{
"day": "2026-09-18",
"index": 100,
"pairs": 14,
"dayChangePct": 0
},
{
"day": "2026-09-19",
"index": 100,
"pairs": 14,
"dayChangePct": 0
},
{
"day": "2026-09-20",
"index": 100,
"pairs": 14,
"dayChangePct": 0
},
{
"day": "2026-09-21",
"index": 100,
"pairs": 15,
"dayChangePct": 0
},
{
"day": "2026-09-22",
"index": 100,
"pairs": 15,
"dayChangePct": 0
},
{
"day": "2026-09-23",
"index": 100,
"pairs": 15,
"dayChangePct": 0
},
{
"day": "2026-09-24",
"index": 100,
"pairs": 15,
"dayChangePct": 0
},
{
"day": "2026-09-25",
"index": 100,
"pairs": 15,
"dayChangePct": 0
},
{
"day": "2026-09-26",
"index": 100,
"pairs": 13,
"dayChangePct": 0
},
{
"day": "2026-09-27",
"index": 100,
"pairs": 13,
"dayChangePct": 0
},
{
"day": "2026-09-28",
"index": 100,
"pairs": 13,
"dayChangePct": 0
},
{
"day": "2026-09-29",
"index": 100,
"pairs": 13,
"dayChangePct": 0
},
{
"day": "2026-09-30",
"index": 100,
"pairs": 13,
"dayChangePct": 0
},
{
"day": "2026-10-01",
"index": 100,
"pairs": 13,
"dayChangePct": 0
},
{
"day": "2026-10-02",
"index": 100,
"pairs": 13,
"dayChangePct": 0
},
{
"day": "2026-10-03",
"index": 100,
"pairs": 13,
"dayChangePct": 0
},
{
"day": "2026-10-04",
"index": 100,
"pairs": 13,
"dayChangePct": 0
},
{
"day": "2026-10-05",
"index": 100,
"pairs": 13,
"dayChangePct": 0
},
{
"day": "2026-10-06",
"index": 100,
"pairs": 13,
"dayChangePct": 0
},
{
"day": "2026-10-07",
"index": 100,
"pairs": 12,
"dayChangePct": 0
},
{
"day": "2026-10-08",
"index": 100,
"pairs": 12,
"dayChangePct": 0
},
{
"day": "2026-10-09",
"index": 100,
"pairs": 12,
"dayChangePct": 0
},
{
"day": "2026-10-10",
"index": 100,
"pairs": 12,
"dayChangePct": 0
},
{
"day": "2026-10-11",
"index": 100,
"pairs": 12,
"dayChangePct": 0
},
{
"day": "2026-10-12",
"index": 100,
"pairs": 10,
"dayChangePct": 0
},
{
"day": "2026-10-13",
"index": 100,
"pairs": 10,
"dayChangePct": 0
},
{
"day": "2026-10-14",
"index": 100,
"pairs": 10,
"dayChangePct": 0
}
],
"latest": 100,
"day_change_pct": 0,
"methodology": "Chained daily price index, base 100 on the first priced scan day (29 Jun 2026). The overall index is the COMPOSITE of the four buyer-tier indices (individual / pro / team&sme / enterprise): each day it moves by the equal-weighted average of the tiers' moves. Each tier index is like-for-like — only agents priced on both consecutive scan days (per-agent ratios, geometric mean, clipped to [0.2, 5]) — so composition changes (agents revealing or hiding prices) can never move it."
},
"top_agents": [
{
"agent_id": "2022",
"name": "2022",
"url": "https://2022.cat/mcp",
"short_summary": "provides AI assistants access to Catalunya 2022 strategic action plan document via MCP protocol",
"price": {
"commercial": {
"currency": "EUR",
"notes": [
"prices in EUR as published; USD figures are conversions at 2026-10-14"
],
"lines": [
{
"name": "Servidor MCP Catalunya 2022",
"price": "0EUR",
"kind": "free",
"billed": "monthly"
}
]
},
"observed": true,
"billing": "free",
"lowest_monthly_usd": null,
"monthly_usd": null,
"headline": "Free",
"summary": "Free. The Catalunya 2022 MCP server is publicly available at no cost, with no authentication required."
},
"evidence_quality": "high",
"upvotes": 0
},
{
"agent_id": "deepwiki_for_agent_zero",
"name": "DeepWiki",
"url": "https://deepwiki.com/agent0ai/agent-zero",
"short_summary": "AI-powered conversational documentation/wiki for the agent-zero GitHub repository; the documented Agent Zero itself is an agentic framework that uses a real OS…",
"price": {
"observed": false,
"billing": "not_found",
"lowest_monthly_usd": null,
"monthly_usd": null,
"headline": "No public price found",
"summary": "No public price found on the vendor site."
},
"evidence_quality": "high",
"upvotes": 0
},
{
"agent_id": "document_intelligence",
"name": "Document Intelligence",
"url": "https://amalgix.io",
"short_summary": "extracts evidence-backed facts from financial filings and contracts with two core workflows: analyze_public_filing for SEC documents and review_contract_risks…",
"price": {
"commercial": {
"rates": [
{
"line": "Pay-Per-Call",
"per": "per call",
"text": "$0.03 per call"
}
],
"currency": "USD",
"lines": [
{
"name": "Pay-Per-Call",
"price": "$0.03 minimum per call",
"kind": "usage_rate",
"unit": "call",
"billed": "usage"
}
]
},
"observed": true,
"billing": "usage",
"lowest_monthly_usd": null,
"monthly_usd": null,
"headline": "$0.03 per call (usage-based)",
"summary": "$0.03 per call (usage-based). Amalgix charges dynamically per document-processing call, starting at $0.03 per call with a stated $79.00 hard safety cap."
},
"evidence_quality": "high",
"upvotes": 0
},
{
"agent_id": "ninjadoc",
"name": "Ninjadoc",
"url": "https://ninjadoc.ai",
"short_summary": "PDF document extraction with visual provenance and citation tracking",
"price": {
"commercial": {
"rates": [
{
"line": "Document Query",
"per": "per page",
"text": "$0.01 per page"
}
],
"currency": "USD",
"notes": [
"prepaid credit: $5 (funding, not a subscription)"
],
"lines": [
{
"name": "1,250 credits",
"price": "$5",
"kind": "credit_purchase",
"unit": "credits",
"billed": "one_off"
},
{
"name": "6,250 credits",
"price": "$25",
"kind": "credit_purchase",
"unit": "credits",
"billed": "one_off"
},
{
"name": "25,000 credits",
"price": "$100",
"kind": "credit_purchase",
"unit": "credits",
"billed": "one_off"
},
{
"name": "125,000 credits",
"price": "$500",
"kind": "credit_purchase",
"unit": "credits",
"billed": "one_off"
},
{
"name": "Document Query",
"price": "$0.01 per page",
"kind": "usage_rate",
"unit": "page",
"billed": "usage"
}
]
},
"observed": true,
"billing": "usage",
"lowest_monthly_usd": null,
"monthly_usd": null,
"headline": "$0.01 per page (usage-based; prepaid credit $5)",
"summary": "$0.01 per page (usage-based; prepaid credit $5). NinjaDoc offers non-expiring credit packs from $5 to $500 with pay-as-you-go document querying at approximately $0.01 per page and no subscriptions."
},
"evidence_quality": "high",
"upvotes": 0
},
{
"agent_id": "shellayer",
"name": "ShelLayer",
"url": "https://shelflayer.com/",
"short_summary": "provides AI agents access to search and retrieve passages from public-domain books with citations",
"price": {
"commercial": {
"currency": "USD",
"lines": [
{
"name": "Beta",
"price": "$ 0 during beta",
"kind": "free",
"billed": "monthly"
},
{
"name": "Pro",
"price": "Coming soon",
"kind": "unknown"
},
{
"name": "Enterprise",
"price": "Contact us",
"kind": "custom"
}
]
},
"observed": true,
"billing": "free",
"lowest_monthly_usd": null,
"monthly_usd": null,
"headline": "Free tier; paid: Coming soon (as published; no rate could be read)",
"summary": "Free tier; paid: Coming soon (as published; no rate could be read). ShelfLayer is free during its public beta, while Pro pricing is not yet announced and Enterprise plans are scoped individually."
},
"evidence_quality": "high",
"upvotes": 0
},
{
"agent_id": "tripitaka_mcp",
"name": "Tripitaka MCP",
"url": "https://tripitaka-mcp.com",
"short_summary": "provides access to the full Pāli Tipiṭaka Buddhist canon with search, translation comparison, and Pāli word lookup capabilities",
"price": {
"commercial": {
"currency": "USD",
"lines": [
{
"name": "Free",
"price": "0USD",
"kind": "free",
"billed": "monthly"
}
]
},
"observed": true,
"billing": "free",
"lowest_monthly_usd": null,
"monthly_usd": null,
"headline": "Free",
"summary": "Free. Tripitaka MCP is offered at no cost, with a $0 offer shown in the page's structured data."
},
"evidence_quality": "high",
"upvotes": 0
},
{
"agent_id": "byteaskai",
"name": "Byteaskai",
"url": "https://docs.byteask.ai/embedded",
"short_summary": "# ByteAsk Embedded Docs MCP\n\nPage-cited retrieval over embedded systems documentation, datasheets, reference manuals, RTOS documentation, coding standards, and…",
"price": {
"observed": false,
"billing": "not_found",
"lowest_monthly_usd": null,
"monthly_usd": null,
"headline": "No public price found",
"summary": "No public price found on the vendor site."
},
"evidence_quality": "medium",
"upvotes": 0
},
{
"agent_id": "corpus",
"name": "Corpus",
"url": "https://mcp.listentosadhu.app",
"short_summary": "Listen to Sadhu exposes a searchable corpus of Vedic scripture and recorded lectures. Look up verses by reference (e.g. \"BG 2.13\", \"SB 5.5.3\", \"CC Madhya 8.128…",
"price": {
"commercial": {
"currency": "USD",
"lines": [
{
"name": "Free",
"price": "Free",
"kind": "free",
"billed": "monthly"
}
]
},
"observed": true,
"billing": "free",
"lowest_monthly_usd": null,
"monthly_usd": null,
"headline": "Free",
"summary": "Free. Listen to Sadhu MCP is presented as a free, public, read-only service with no subscription price shown."
},
"evidence_quality": "medium",
"upvotes": 0
},
{
"agent_id": "foiagras_mcp",
"name": "Foiagras",
"url": "https://foiagras.com/mcp/",
"short_summary": "searches a public records database for documents, meeting minutes, and investigative reporting on behalf of an AI assistant",
"price": {
"observed": false,
"billing": "not_found",
"lowest_monthly_usd": null,
"monthly_usd": null,
"headline": "No public price found",
"summary": "No public price found on the vendor site."
},
"evidence_quality": "medium",
"upvotes": 0
},
{
"agent_id": "iching_rocks",
"name": "Iching Rocks",
"url": "https://iching.rocks/mcp",
"short_summary": "Public, read-only MCP over the complete 64-hexagram I Ching corpus — hexagrams, trigrams, changing lines, and reading context from an original English translat…",
"price": {
"observed": false,
"billing": "not_found",
"lowest_monthly_usd": null,
"monthly_usd": null,
"headline": "No public price found",
"summary": "No public pricing for IChing.Rocks was observed on the homepage."
},
"evidence_quality": "medium",
"upvotes": 0
}
],
"platforms_also_here": [
{
"agent_id": "alpha_sense_developer",
"name": "Alpha Sense Developer",
"url": "https://developer.alpha-sense.com/",
"short_summary": "provides AI agents access to enterprise intelligence for search, research and summarization workflows like meeting prep and idea generation",
"price": {
"observed": false,
"billing": "not_found",
"lowest_monthly_usd": null,
"monthly_usd": null,
"headline": "No public price found",
"summary": "No public pricing amounts or plan details are shown in the supplied AlphaSense Developer Portal homepage context."
},
"home_niche": "developer-portal-api-docs",
"also_covers": true,
"upvotes": 0
},
{
"agent_id": "kappa_graph",
"name": "Kappa Graph",
"url": "https://aaronsb.github.io/knowledge-graph-system/",
"short_summary": "Multi-dimensional knowledge extraction system that ingests documents, extracts concepts and relationships via LLM, stores them in a graph database, and exposes…",
"price": {
"commercial": {
"rates": [
{
"line": "Estimated extraction cost",
"per": "per unit",
"text": "$0 per unit"
}
],
"currency": "USD",
"lines": [
{
"name": "Estimated extraction cost",
"price": "$0.003",
"kind": "usage_rate",
"unit": "unit",
"billed": "usage"
}
]
},
"observed": true,
"billing": "usage",
"lowest_monthly_usd": null,
"monthly_usd": null,
"headline": "$0 per unit (usage-based)",
"summary": "$0 per unit (usage-based). The tutorial shows an estimated usage cost of $0.003 for an ingestion job, with no subscription plans publicly listed."
},
"home_niche": "knowledge-graph-agent",
"also_covers": true,
"upvotes": 0
},
{
"agent_id": "plasma_wiki",
"name": "Plasma Wiki",
"url": "https://github.com/plasma-ai/wiki",
"short_summary": "Indexed knowledge bases with command-line tools for agents. Creates structured markdown wikis that agents can query to ground their work in project-specific kn…",
"price": {
"observed": false,
"billing": "not_found",
"lowest_monthly_usd": null,
"monthly_usd": null,
"headline": "No public price found",
"summary": "No public pricing is shown on the GitHub homepage or in the supplied context."
},
"home_niche": "enterprise-knowledge-platform",
"also_covers": true,
"upvotes": 0
},
{
"agent_id": "veridive",
"name": "Veridive",
"url": "https://veridive.com",
"short_summary": "answers questions by searching and retrieving information from spoken/video content like podcasts and YouTube videos",
"price": {
"commercial": {
"entry_offer": {
"line": "Pro",
"monthly_native": 3.9,
"monthly_usd": 3.9,
"commitment": "monthly",
"basis": "$3.9/month",
"billing_verified": true
},
"annual_option": {
"line": "Pro (annual billing)",
"monthly_equivalent_native": 3.33,
"total_native": 39.96
},
"currency": "USD",
"notes": [
"prepaid credit: $7.90 (funding, not a subscription)"
],
"lines": [
{
"name": "Free",
"price": "$0",
"kind": "free",
"billed": "monthly"
},
{
"name": "Pro",
"price": "$3.90/mo",
"kind": "base_subscription",
"billed": "monthly"
},
{
"name": "Pro (annual billing)",
"price": "$3.33/mo billed yearly",
"kind": "base_subscription",
"billed": "annually"
},
{
"name": "Top-up pack — 5,000 credits",
"price": "$7.90",
"kind": "credit_purchase",
"billed": "one_off"
},
{
"name": "Top-up pack — 10,000 credits",
"price": "$14.90",
"kind": "credit_purchase",
"billed": "one_off"
},
{
"name": "Top-up pack — 20,000 credits",
"price": "$24.90",
"kind": "credit_purchase",
"billed": "one_off"
},
{
"name": "Top-up pack — 50,000 credits",
"price": "$44.90",
"kind": "credit_purchase",
"billed": "one_off"
}
]
},
"observed": true,
"billing": "freemium",
"lowest_monthly_usd": 3.9,
"monthly_usd": 3.9,
"headline": "Free plan; paid from $3.9/mo; $3.33/mo equivalent billed annually",
"summary": "Free plan; paid from $3.9/mo; $3.33/mo equivalent billed annually. Veridive offers a permanent free plan, a $3.90/month Pro subscription or $39.90/year annual billing, plus one-time credit top-ups."
},
"home_niche": "video-avatar-generation",
"also_covers": true,
"upvotes": 0
}
],
"page_url": "https://agentery.com/market/document-qa-agent",
"summary": {
"niche": "document-qa-agent",
"sector": "research-knowledge-work",
"pricing_by_provider_type": {
"headline": "Prices differ by provider type and buyer tier — no blended headline is used. Strongest cohort: Agents · Pro median $16/mo (7 providers). See benchmarks_by_provider_type_and_tier for the full matrix.",
"benchmarks": [
{
"provider_type": "agent",
"provider_type_label": "Agents",
"buyer_tier": "pro",
"buyer_tier_label": "Pro",
"pricing_unit": "flat",
"pricing_unit_label": "flat monthly",
"comparable_provider_count": 7,
"reliability": "medium",
"median": 16,
"p25": 13.99,
"p75": 34,
"status": "ok"
},
{
"provider_type": "agent",
"provider_type_label": "Agents",
"buyer_tier": "individual",
"buyer_tier_label": "Individual",
"pricing_unit": "flat",
"pricing_unit_label": "flat monthly",
"comparable_provider_count": 5,
"reliability": "medium",
"median": 12.99,
"p25": 6,
"p75": 19,
"status": "ok"
},
{
"provider_type": "agent",
"provider_type_label": "Agents",
"buyer_tier": "team_sme",
"buyer_tier_label": "Team / SME",
"pricing_unit": "flat",
"pricing_unit_label": "flat monthly",
"comparable_provider_count": 3,
"reliability": "low",
"median": 129,
"p25": null,
"p75": null,
"status": "median_only"
}
],
"warnings": [
"This niche currently has sufficient agent pricing but insufficient MCP pricing."
],
"full_pricing_via": {
"tool": "price_benchmark",
"arguments": {
"niche": "document-qa-agent"
},
"note": "add provider_type + buyer_tier for a specific cohort"
}
},
"page_url": "https://agentery.com/market/document-qa-agent",
"counts": {
"listings_with_price_capture": 49,
"listings_with_observed_public_price": 21,
"providers_with_numeric_monthly_price_latest_scan": 9,
"like_for_like_comparable_pairs": 8
},
"movement": {
"d": {
"published": false,
"value_pct": null,
"held_reason": null
},
"w": {
"published": false,
"value_pct": null,
"held_reason": null
},
"m": {
"published": false,
"value_pct": null,
"held_reason": null
}
},
"pricing_version": "cohorts-1",
"pricing_status": "ok",
"pricing_by_tier": [
{
"tier": "individual",
"currency": "USD",
"period": "month",
"unit": "flat",
"median": 12.99,
"provider_count": 5,
"plan_observation_count": 6,
"data_confidence": 0.39,
"data_confidence_basis": {
"provider_component": 0.42,
"observation_component": 0.3,
"provider_count": 5,
"plan_observation_count": 6
},
"reliability": "medium",
"members": [
{
"provider": "ekstrakt",
"usd": 5.5
},
{
"provider": "smry",
"usd": 6
},
{
"provider": "skipit",
"usd": 12.99
},
{
"provider": "boei_pdf_ai",
"usd": 19
},
{
"provider": "hyperwrite_text_extractor",
"usd": 29
}
],
"p25": 6,
"p75": 19
},
{
"tier": "pro",
"currency": "USD",
"period": "month",
"unit": "flat",
"median": 16,
"provider_count": 7,
"plan_observation_count": 7,
"data_confidence": 0.54,
"data_confidence_basis": {
"provider_component": 0.58,
"observation_component": 0.35,
"provider_count": 7,
"plan_observation_count": 7
},
"reliability": "medium",
"members": [
{
"provider": "1min_ai_pdf_chat",
"usd": 6.5
},
{
"provider": "aiagentdocs",
"usd": 12.99
},
{
"provider": "pdfpeer",
"usd": 14.99
},
{
"provider": "hyperwrite_text_extractor",
"usd": 16
},
{
"provider": "google_drive_rag_agent",
"usd": 29
},
{
"provider": "ai_drive",
"usd": 39
},
{
"provider": "smry",
"usd": 80
}
],
"p25": 13.99,
"p75": 34
},
{
"tier": "team_sme",
"currency": "USD",
"period": "month",
"unit": "flat",
"median": 129,
"provider_count": 3,
"plan_observation_count": 5,
"data_confidence": 0.25,
"data_confidence_basis": {
"provider_component": 0.25,
"observation_component": 0.25,
"provider_count": 3,
"plan_observation_count": 5
},
"reliability": "low",
"members": [
{
"provider": "1min_ai_pdf_chat",
"usd": 10
},
{
"provider": "boei_pdf_ai",
"usd": 129
},
{
"provider": "ai_drive",
"usd": 200
}
]
}
],
"pricing_coverage": {
"listings_with_price_capture": 49,
"listings_with_observed_public_price": 21,
"normalized_observations": 19,
"comparable_providers": 10,
"strict_cohorts": 3,
"exclusion_reasons": {
"promo": 1,
"ambiguous_cadence": 5,
"usage_not_monthly": 5,
"one_time": 4
}
},
"pricing_note": "Provider-deduped, FX-normalized monthly medians, separated by buyer tier AND billing unit (flat/per_seat/per_user/per_agent) — incompatible units are never blended. Ranges (p25/p75) only at >=5 providers; data_confidence is provider-count-weighted. Usage-metered, promo, range, one-time and ambiguous-cadence plans are excluded.",
"pricing_excluded_observations": {
"promo": 1,
"ambiguous_cadence": 5,
"usage_not_monthly": 5,
"one_time": 4
},
"billing_mix": {
"freemium": 6,
"usage": 3,
"subscription": 4,
"free": 8
},
"free_tier_share": 0.67,
"top_providers": [
{
"agent_id": "2022",
"name": "2022",
"price": {
"commercial": {
"currency": "EUR",
"notes": [
"prices in EUR as published; USD figures are conversions at 2026-10-14"
],
"lines": [
{
"name": "Servidor MCP Catalunya 2022",
"price": "0EUR",
"kind": "free",
"billed": "monthly"
}
]
},
"observed": true,
"billing": "free",
"lowest_monthly_usd": null,
"monthly_usd": null,
"headline": "Free",
"summary": "Free. The Catalunya 2022 MCP server is publicly available at no cost, with no authentication required."
},
"observed": true
},
{
"agent_id": "deepwiki_for_agent_zero",
"name": "DeepWiki",
"price": {
"observed": false,
"billing": "not_found",
"lowest_monthly_usd": null,
"monthly_usd": null,
"headline": "No public price found",
"summary": "No public price found on the vendor site."
},
"observed": false
},
{
"agent_id": "document_intelligence",
"name": "Document Intelligence",
"price": {
"commercial": {
"rates": [
{
"line": "Pay-Per-Call",
"per": "per call",
"text": "$0.03 per call"
}
],
"currency": "USD",
"lines": [
{
"name": "Pay-Per-Call",
"price": "$0.03 minimum per call",
"kind": "usage_rate",
"unit": "call",
"billed": "usage"
}
]
},
"observed": true,
"billing": "usage",
"lowest_monthly_usd": null,
"monthly_usd": null,
"headline": "$0.03 per call (usage-based)",
"summary": "$0.03 per call (usage-based). Amalgix charges dynamically per document-processing call, starting at $0.03 per call with a stated $79.00 hard safety cap."
},
"observed": true
},
{
"agent_id": "ninjadoc",
"name": "Ninjadoc",
"price": {
"commercial": {
"rates": [
{
"line": "Document Query",
"per": "per page",
"text": "$0.01 per page"
}
],
"currency": "USD",
"notes": [
"prepaid credit: $5 (funding, not a subscription)"
],
"lines": [
{
"name": "1,250 credits",
"price": "$5",
"kind": "credit_purchase",
"unit": "credits",
"billed": "one_off"
},
{
"name": "6,250 credits",
"price": "$25",
"kind": "credit_purchase",
"unit": "credits",
"billed": "one_off"
},
{
"name": "25,000 credits",
"price": "$100",
"kind": "credit_purchase",
"unit": "credits",
"billed": "one_off"
},
{
"name": "125,000 credits",
"price": "$500",
"kind": "credit_purchase",
"unit": "credits",
"billed": "one_off"
},
{
"name": "Document Query",
"price": "$0.01 per page",
"kind": "usage_rate",
"unit": "page",
"billed": "usage"
}
]
},
"observed": true,
"billing": "usage",
"lowest_monthly_usd": null,
"monthly_usd": null,
"headline": "$0.01 per page (usage-based; prepaid credit $5)",
"summary": "$0.01 per page (usage-based; prepaid credit $5). NinjaDoc offers non-expiring credit packs from $5 to $500 with pay-as-you-go document querying at approximately $0.01 per page and no subscriptions."
},
"observed": true
},
{
"agent_id": "shellayer",
"name": "ShelLayer",
"price": {
"commercial": {
"currency": "USD",
"lines": [
{
"name": "Beta",
"price": "$ 0 during beta",
"kind": "free",
"billed": "monthly"
},
{
"name": "Pro",
"price": "Coming soon",
"kind": "unknown"
},
{
"name": "Enterprise",
"price": "Contact us",
"kind": "custom"
}
]
},
"observed": true,
"billing": "free",
"lowest_monthly_usd": null,
"monthly_usd": null,
"headline": "Free tier; paid: Coming soon (as published; no rate could be read)",
"summary": "Free tier; paid: Coming soon (as published; no rate could be read). ShelfLayer is free during its public beta, while Pro pricing is not yet announced and Enterprise plans are scoped individually."
},
"observed": true
}
],
"suggested_next_calls": [
{
"tool": "price_benchmark",
"arguments": {
"niche": "document-qa-agent"
},
"purpose": "full observed price distribution + per-tier medians for this niche"
},
{
"tool": "niche_report",
"arguments": {
"niche": "document-qa-agent",
"response_mode": "full"
},
"purpose": "the complete report incl. index series and tier decomposition"
},
{
"tool": "suggest_alternatives",
"arguments": {
"agent_id": "2022"
},
"purpose": "comparable (optionally cheaper) providers to a named agent"
},
{
"tool": "get_agent_profile",
"arguments": {
"agent_id": "2022"
},
"purpose": "full profile, integrations and pricing for one provider"
}
]
}
}Full market
18 providers, one sortable view
Dense enough for many listings; progressive disclosure keeps mobile usable.
ProviderTypeFromVs niche medianLiveness
2022provides AI assistants access to Catalunya 2022 strategic action plan document via MCP protocol
ShelLayerprovides AI agents access to search and retrieve passages from public-domain books with citations
Tripitaka MCPprovides access to the full Pāli Tipiṭaka Buddhist canon with search, translation comparison, and Pāli word lookup capabilitiesCCorpusListen to Sadhu exposes a searchable corpus of Vedic scripture and recorded lectures. Look up verses by reference (e.g. "BG 2.13", "SB 5.5.3", "CC Madhya 8.128…
mcpFreefree to use—88% live
1min Ai Pdf ChatAI-powered PDF chat tool that allows users to ask questions and get instant answers from PDF documents. Supports multiple AI models including GPT-4, Claude, an…
Ai DriveDocument intelligence platform for legal and professional workflows. Upload PDFs, Word docs, and images to get AI-powered analysis, summaries, and insights. Fe…
AiagentdocsAI-powered document intelligence tool that lets users upload PDFs and Word documents to get instant answers, summaries, and insights through natural language c…
Boei Pdf AiTransforms static PDF documents into interactive AI agents that answer questions about document content in real-time. Users can ask questions in natural langua…
Document Qa AssistantAI agent that answers questions by searching through and analyzing uploaded documents. Enables users to query their document collections for specific informati…
Google Drive Rag AgentAI agent that monitors Google Drive folders, automatically indexes documents using OpenAI embeddings and Pinecone, and provides conversational Q&A with memory.…
Hipdf Ai AgentAI agent that reads, analyzes, and summarizes PDF documents. Automatically selects optimal AI models (GPT/Claude/Gemini) for different PDF tasks. Supports Q&A,…
Hyperwrite Text ExtractorAI-powered text analysis tool that extracts key details, main points, and important facts from complex texts. Helps researchers, students, writers, and profess…NMNotebooklm Mcp 4MCP server and REST API for Google NotebookLM. Enables citation-backed Q&A, audio/video/content generation, and multi-account rotation. Integrates with Claude,…
mcpFreefree to use—88% live
Pdf Mcp 2Open-source MCP server enabling AI agents to efficiently read, search, and analyze PDFs without loading entire documents into context. Supports hybrid search,…
PdfpeerAI-powered PDF chat tool that allows users to upload documents and interact with them through natural language queries. Supports summarization, Q&A, and inform…Showing only providers with a published price or a free plan. $29 = lowest observed monthly · Free = free to use · Free tier = free plan + paid options.