Rank
83
A Model Context Protocol (MCP) server for GitLab
Traction
No public download signal
Freshness
Updated 2d ago
Crawler Summary
# Hyperplexity — AI Research Tables with Citations and Confidence Scores **Turn a prompt into a verified, cited research table. Or fact-check any table or document you already have.** Hyperplexity gives Claude the ability to conduct deep, structured research across entire domains — not one question at a time, but hundreds of cells simultaneously, each with a sourced answer, a confidence rating, and links to the evidence. --- ## What it does You describe what you want in plain English. Hyperplexity researches it, validates every fact, and returns a structured table where each cell has: - ✅ A verified answer - 📊 A confidence score (HIGH / MEDIUM / LOW) - 🔗 Citations to the actual sources The output is an Excel file and a shareable interactive viewer. Claude drives the full workflow — you just review and approve. --- ## Three ways to start Once installed, tell Claude what you want in plain English — it drives everything from there. | Goal | What to say to Claude | |------|----------------------| | **Generate a table from a prompt** | *"Use Hyperplexity to create a table of the top 20 US biotech companies with columns: company, market cap, lead drug, and phase."* | | **Validate an existing Excel or CSV** | *"Use Hyperplexity to validate `companies.xlsx`. Interview me about what each column means, then run the preview."* | | **Fact-check a document or passage** | *"Use Hyperplexity to fact-check this analyst report."* *(paste text or share a file path)* | Claude handles the full workflow — upload, configure, preview, approve — pausing only when a decision genuinely needs you. --- ## What each workflow does ### Generate a table from a prompt Claude starts a table-maker session, clarifies the structure if needed, builds the table, runs a free 3-row preview, and waits for your approval before billing. ### Validate an existing Excel or CSV file Upload any table and Hyperplexity fact-checks every cell against live sources. It learns the meaning of your columns through a short interview (or you can skip the interview entirely with a one-line description), then runs the same preview-then-approve flow. ### Fact-check a document or text passage Paste an analyst report, a research abstract, or any text with factual claims. Hyperplexity extracts each claim, verifies it independently, and returns support levels: **SUPPORTED / PARTIAL / UNSUPPORTED / UNVERIFIABLE** — with the source for every verdict. ### Refresh a table you already ran Re-run validation on any prior job to pick up changes in source data. No re-upload or configuration needed. --- ## Why it's different Most AI tools answer one question at a time. Hyperplexity answers a whole research domain at once — running hundreds of targeted searches, applying QC passes, and reconciling conflicting sources — then packages the results into a structured, citable format. The MCP integration means Claude can drive the entire workflow autonomously: upload, configure, preview, approve, and retrieve results — pausing only when a decision genuinely requires human input. --- ## Pricing | | Cost | |--|--| | Preview (first 3 rows) | Free | | Standard validation | ~$0.05 / cell | | Advanced validation | up to ~$0.25 / cell | | Minimum per run | $2.00 | New accounts get **$20 in free credits** — enough for several full tables. --- ## Get started 1. Get your API key at [hyperplexity.ai/account](https://hyperplexity.ai/account) 2. Install the MCP server: **Option A — uvx (recommended):** ```bash claude mcp add hyperplexity uvx mcp-server-hyperplexity \ -e HYPERPLEXITY_API_KEY=hpx_live_your_key_here ``` **Option B — Direct HTTP to Railway:** ```bash claude mcp add hyperplexity \ --transport http \ https://mcp-server-hyperplexity-production.up.railway.app/ \ --header "X-Api-Key: hpx_live_your_key_here" ``` **Option C — Smithery** (for OpenClaw and other Smithery-compatible clients): ```bash npx -y @smithery/cli@latest login npx -y @smithery/cli@latest mcp add hyperplexity/hyperplexity --client claude-code ``` Then open your client → `/mcp` → **hyperplexity → Authenticate** → enter your API key. 3. Ask your agent: *"Use Hyperplexity to generate a table of…"* Full documentation: [eliyahu.ai/api-guide](https://eliyahu.ai/api-guide) Hyperplexity — AI Research Tables with Citations and Confidence Scores **Turn a prompt into a verified, cited research table. Or fact-check any table or document you already have.** Hyperplexity gives Claude the ability to conduct deep, structured research across entire domains — not one question at a time, but hundreds of cells simultaneously, each with a sourced answer, a confidence rating, and links to the evidenc Capability contract not published. No trust telemetry is available yet. Last updated 4/16/2026.
Freshness
Last checked 4/16/2026
Best For
Hyperplexity is best for general automation workflows where MCP compatibility matters.
Not Ideal For
Contract metadata is missing or unavailable for deterministic execution.
Evidence Sources Checked
editorial-content, Smithery, runtime-metrics, public facts pack
# Hyperplexity — AI Research Tables with Citations and Confidence Scores **Turn a prompt into a verified, cited research table. Or fact-check any table or document you already have.** Hyperplexity gives Claude the ability to conduct deep, structured research across entire domains — not one question at a time, but hundreds of cells simultaneously, each with a sourced answer, a confidence rating, and links to the evidence. --- ## What it does You describe what you want in plain English. Hyperplexity researches it, validates every fact, and returns a structured table where each cell has: - ✅ A verified answer - 📊 A confidence score (HIGH / MEDIUM / LOW) - 🔗 Citations to the actual sources The output is an Excel file and a shareable interactive viewer. Claude drives the full workflow — you just review and approve. --- ## Three ways to start Once installed, tell Claude what you want in plain English — it drives everything from there. | Goal | What to say to Claude | |------|----------------------| | **Generate a table from a prompt** | *"Use Hyperplexity to create a table of the top 20 US biotech companies with columns: company, market cap, lead drug, and phase."* | | **Validate an existing Excel or CSV** | *"Use Hyperplexity to validate `companies.xlsx`. Interview me about what each column means, then run the preview."* | | **Fact-check a document or passage** | *"Use Hyperplexity to fact-check this analyst report."* *(paste text or share a file path)* | Claude handles the full workflow — upload, configure, preview, approve — pausing only when a decision genuinely needs you. --- ## What each workflow does ### Generate a table from a prompt Claude starts a table-maker session, clarifies the structure if needed, builds the table, runs a free 3-row preview, and waits for your approval before billing. ### Validate an existing Excel or CSV file Upload any table and Hyperplexity fact-checks every cell against live sources. It learns the meaning of your columns through a short interview (or you can skip the interview entirely with a one-line description), then runs the same preview-then-approve flow. ### Fact-check a document or text passage Paste an analyst report, a research abstract, or any text with factual claims. Hyperplexity extracts each claim, verifies it independently, and returns support levels: **SUPPORTED / PARTIAL / UNSUPPORTED / UNVERIFIABLE** — with the source for every verdict. ### Refresh a table you already ran Re-run validation on any prior job to pick up changes in source data. No re-upload or configuration needed. --- ## Why it's different Most AI tools answer one question at a time. Hyperplexity answers a whole research domain at once — running hundreds of targeted searches, applying QC passes, and reconciling conflicting sources — then packages the results into a structured, citable format. The MCP integration means Claude can drive the entire workflow autonomously: upload, configure, preview, approve, and retrieve results — pausing only when a decision genuinely requires human input. --- ## Pricing | | Cost | |--|--| | Preview (first 3 rows) | Free | | Standard validation | ~$0.05 / cell | | Advanced validation | up to ~$0.25 / cell | | Minimum per run | $2.00 | New accounts get **$20 in free credits** — enough for several full tables. --- ## Get started 1. Get your API key at [hyperplexity.ai/account](https://hyperplexity.ai/account) 2. Install the MCP server: **Option A — uvx (recommended):** ```bash claude mcp add hyperplexity uvx mcp-server-hyperplexity \ -e HYPERPLEXITY_API_KEY=hpx_live_your_key_here ``` **Option B — Direct HTTP to Railway:** ```bash claude mcp add hyperplexity \ --transport http \ https://mcp-server-hyperplexity-production.up.railway.app/ \ --header "X-Api-Key: hpx_live_your_key_here" ``` **Option C — Smithery** (for OpenClaw and other Smithery-compatible clients): ```bash npx -y @smithery/cli@latest login npx -y @smithery/cli@latest mcp add hyperplexity/hyperplexity --client claude-code ``` Then open your client → `/mcp` → **hyperplexity → Authenticate** → enter your API key. 3. Ask your agent: *"Use Hyperplexity to generate a table of…"* Full documentation: [eliyahu.ai/api-guide](https://eliyahu.ai/api-guide) Hyperplexity — AI Research Tables with Citations and Confidence Scores **Turn a prompt into a verified, cited research table. Or fact-check any table or document you already have.** Hyperplexity gives Claude the ability to conduct deep, structured research across entire domains — not one question at a time, but hundreds of cells simultaneously, each with a sourced answer, a confidence rating, and links to the evidenc
Public facts
3
Change events
0
Artifacts
0
Freshness
Apr 16, 2026
Capability contract not published. No trust telemetry is available yet. Last updated 4/16/2026.
Trust score
Unknown
Compatibility
MCP
Freshness
Apr 16, 2026
Vendor
Hyperplexity
Artifacts
0
Benchmarks
0
Last release
Unpublished
Key links, install path, and a quick operational read before the deeper crawl record.
Summary
Capability contract not published. No trust telemetry is available yet. Last updated 4/16/2026.
Setup snapshot
Setup complexity is LOW. This package is likely designed for quick installation with minimal external side-effects.
Final validation: Expose the agent to a mock request payload inside a sandbox and trace the network egress before allowing access to real customer data.
Everything public we have scraped or crawled about this agent, grouped by evidence type with provenance.
Vendor
Hyperplexity
Protocol compatibility
MCP
Handshake status
UNKNOWN
Merged public release, docs, artifact, benchmark, pricing, and trust refresh events.
Extracted files, examples, snippets, parameters, dependencies, permissions, and artifact metadata.
Extracted files
0
Examples
3
Snippets
0
Languages
Unknown
bash
claude mcp add hyperplexity uvx mcp-server-hyperplexity \ -e HYPERPLEXITY_API_KEY=hpx_live_your_key_here
bash
claude mcp add hyperplexity \ --transport http \ https://mcp-server-hyperplexity-production.up.railway.app/ \ --header "X-Api-Key: hpx_live_your_key_here"
bash
npx -y @smithery/cli@latest login npx -y @smithery/cli@latest mcp add hyperplexity/hyperplexity --client claude-code
Full documentation captured from public sources, including the complete README when available.
Docs source
Smithery
Editorial quality
ready
# Hyperplexity — AI Research Tables with Citations and Confidence Scores **Turn a prompt into a verified, cited research table. Or fact-check any table or document you already have.** Hyperplexity gives Claude the ability to conduct deep, structured research across entire domains — not one question at a time, but hundreds of cells simultaneously, each with a sourced answer, a confidence rating, and links to the evidence. --- ## What it does You describe what you want in plain English. Hyperplexity researches it, validates every fact, and returns a structured table where each cell has: - ✅ A verified answer - 📊 A confidence score (HIGH / MEDIUM / LOW) - 🔗 Citations to the actual sources The output is an Excel file and a shareable interactive viewer. Claude drives the full workflow — you just review and approve. --- ## Three ways to start Once installed, tell Claude what you want in plain English — it drives everything from there. | Goal | What to say to Claude | |------|----------------------| | **Generate a table from a prompt** | *"Use Hyperplexity to create a table of the top 20 US biotech companies with columns: company, market cap, lead drug, and phase."* | | **Validate an existing Excel or CSV** | *"Use Hyperplexity to validate `companies.xlsx`. Interview me about what each column means, then run the preview."* | | **Fact-check a document or passage** | *"Use Hyperplexity to fact-check this analyst report."* *(paste text or share a file path)* | Claude handles the full workflow — upload, configure, preview, approve — pausing only when a decision genuinely needs you. --- ## What each workflow does ### Generate a table from a prompt Claude starts a table-maker session, clarifies the structure if needed, builds the table, runs a free 3-row preview, and waits for your approval before billing. ### Validate an existing Excel or CSV file Upload any table and Hyperplexity fact-checks every cell against live sources. It learns the meaning of your columns through a short interview (or you can skip the interview entirely with a one-line description), then runs the same preview-then-approve flow. ### Fact-check a document or text passage Paste an analyst report, a research abstract, or any text with factual claims. Hyperplexity extracts each claim, verifies it independently, and returns support levels: **SUPPORTED / PARTIAL / UNSUPPORTED / UNVERIFIABLE** — with the source for every verdict. ### Refresh a table you already ran Re-run validation on any prior job to pick up changes in source data. No re-upload or configuration needed. --- ## Why it's different Most AI tools answer one question at a time. Hyperplexity answers a whole research domain at once — running hundreds of targeted searches, applying QC passes, and reconciling conflicting sources — then packages the results into a structured, citable format. The MCP integration means Claude can drive the entire workflow autonomously: upload, configure, preview, approve, and retrieve results — pausing only when a decision genuinely requires human input. --- ## Pricing | | Cost | |--|--| | Preview (first 3 rows) | Free | | Standard validation | ~$0.05 / cell | | Advanced validation | up to ~$0.25 / cell | | Minimum per run | $2.00 | New accounts get **$20 in free credits** — enough for several full tables. --- ## Get started 1. Get your API key at [hyperplexity.ai/account](https://hyperplexity.ai/account) 2. Install the MCP server: **Option A — uvx (recommended):** ```bash claude mcp add hyperplexity uvx mcp-server-hyperplexity \ -e HYPERPLEXITY_API_KEY=hpx_live_your_key_here ``` **Option B — Direct HTTP to Railway:** ```bash claude mcp add hyperplexity \ --transport http \ https://mcp-server-hyperplexity-production.up.railway.app/ \ --header "X-Api-Key: hpx_live_your_key_here" ``` **Option C — Smithery** (for OpenClaw and other Smithery-compatible clients): ```bash npx -y @smithery/cli@latest login npx -y @smithery/cli@latest mcp add hyperplexity/hyperplexity --client claude-code ``` Then open your client → `/mcp` → **hyperplexity → Authenticate** → enter your API key. 3. Ask your agent: *"Use Hyperplexity to generate a table of…"* Full documentation: [eliyahu.ai/api-guide](https://eliyahu.ai/api-guide) Hyperplexity — AI Research Tables with Citations and Confidence Scores **Turn a prompt into a verified, cited research table. Or fact-check any table or document you already have.** Hyperplexity gives Claude the ability to conduct deep, structured research across entire domains — not one question at a time, but hundreds of cells simultaneously, each with a sourced answer, a confidence rating, and links to the evidenc
Turn a prompt into a verified, cited research table. Or fact-check any table or document you already have.
Hyperplexity gives Claude the ability to conduct deep, structured research across entire domains — not one question at a time, but hundreds of cells simultaneously, each with a sourced answer, a confidence rating, and links to the evidence.
You describe what you want in plain English. Hyperplexity researches it, validates every fact, and returns a structured table where each cell has:
The output is an Excel file and a shareable interactive viewer. Claude drives the full workflow — you just review and approve.
Once installed, tell Claude what you want in plain English — it drives everything from there.
| Goal | What to say to Claude |
|------|----------------------|
| Generate a table from a prompt | "Use Hyperplexity to create a table of the top 20 US biotech companies with columns: company, market cap, lead drug, and phase." |
| Validate an existing Excel or CSV | "Use Hyperplexity to validate companies.xlsx. Interview me about what each column means, then run the preview." |
| Fact-check a document or passage | "Use Hyperplexity to fact-check this analyst report." (paste text or share a file path) |
Claude handles the full workflow — upload, configure, preview, approve — pausing only when a decision genuinely needs you.
Claude starts a table-maker session, clarifies the structure if needed, builds the table, runs a free 3-row preview, and waits for your approval before billing.
Upload any table and Hyperplexity fact-checks every cell against live sources. It learns the meaning of your columns through a short interview (or you can skip the interview entirely with a one-line description), then runs the same preview-then-approve flow.
Paste an analyst report, a research abstract, or any text with factual claims. Hyperplexity extracts each claim, verifies it independently, and returns support levels: SUPPORTED / PARTIAL / UNSUPPORTED / UNVERIFIABLE — with the source for every verdict.
Re-run validation on any prior job to pick up changes in source data. No re-upload or configuration needed.
Most AI tools answer one question at a time. Hyperplexity answers a whole research domain at once — running hundreds of targeted searches, applying QC passes, and reconciling conflicting sources — then packages the results into a structured, citable format.
The MCP integration means Claude can drive the entire workflow autonomously: upload, configure, preview, approve, and retrieve results — pausing only when a decision genuinely requires human input.
| | Cost | |--|--| | Preview (first 3 rows) | Free | | Standard validation | ~$0.05 / cell | | Advanced validation | up to ~$0.25 / cell | | Minimum per run | $2.00 |
New accounts get $20 in free credits — enough for several full tables.
Option A — uvx (recommended):
claude mcp add hyperplexity uvx mcp-server-hyperplexity \
-e HYPERPLEXITY_API_KEY=hpx_live_your_key_here
Option B — Direct HTTP to Railway:
claude mcp add hyperplexity \
--transport http \
https://mcp-server-hyperplexity-production.up.railway.app/ \
--header "X-Api-Key: hpx_live_your_key_here"
Option C — Smithery (for OpenClaw and other Smithery-compatible clients):
npx -y @smithery/cli@latest login
npx -y @smithery/cli@latest mcp add hyperplexity/hyperplexity --client claude-code
Then open your client → /mcp → hyperplexity → Authenticate → enter your API key.
Full documentation: eliyahu.ai/api-guide
Machine endpoints, protocol fit, contract coverage, invocation examples, and guardrails for agent-to-agent use.
Contract coverage
Status
missing
Auth
None
Streaming
No
Data region
Unspecified
Protocol support
Requires: none
Forbidden: none
Guardrails
Operational confidence: low
curl -s "https://xpersona.co/api/v1/agents/smithery-hyperplexity-production/snapshot"
curl -s "https://xpersona.co/api/v1/agents/smithery-hyperplexity-production/contract"
curl -s "https://xpersona.co/api/v1/agents/smithery-hyperplexity-production/trust"
Trust and runtime signals, benchmark suites, failure patterns, and practical risk constraints.
Trust signals
Handshake
UNKNOWN
Confidence
unknown
Attempts 30d
unknown
Fallback rate
unknown
Runtime metrics
Observed P50
unknown
Observed P95
unknown
Rate limit
unknown
Estimated cost
unknown
Do not use if
Every public screenshot, visual asset, demo link, and owner-provided destination tied to this agent.
Neighboring agents from the same protocol and source ecosystem for comparison and shortlist building.
Rank
83
A Model Context Protocol (MCP) server for GitLab
Traction
No public download signal
Freshness
Updated 2d ago
Rank
80
A Model Context Protocol (MCP) server for GitLab
Traction
No public download signal
Freshness
Updated 2d ago
Rank
74
Expose OpenAPI definition endpoints as MCP tools using the official Rust SDK for the Model Context Protocol (https://github.com/modelcontextprotocol/rust-sdk)
Traction
No public download signal
Freshness
Updated 2d ago
Rank
72
An actix_web backend for the official Rust SDK for the Model Context Protocol (https://github.com/modelcontextprotocol/rust-sdk)
Traction
No public download signal
Freshness
Updated 2d ago
Contract JSON
{
"contractStatus": "missing",
"authModes": [],
"requires": [],
"forbidden": [],
"supportsMcp": false,
"supportsA2a": false,
"supportsStreaming": false,
"inputSchemaRef": null,
"outputSchemaRef": null,
"dataRegion": null,
"contractUpdatedAt": null,
"sourceUpdatedAt": null,
"freshnessSeconds": null
}Invocation Guide
{
"preferredApi": {
"snapshotUrl": "https://xpersona.co/api/v1/agents/smithery-hyperplexity-production/snapshot",
"contractUrl": "https://xpersona.co/api/v1/agents/smithery-hyperplexity-production/contract",
"trustUrl": "https://xpersona.co/api/v1/agents/smithery-hyperplexity-production/trust"
},
"curlExamples": [
"curl -s \"https://xpersona.co/api/v1/agents/smithery-hyperplexity-production/snapshot\"",
"curl -s \"https://xpersona.co/api/v1/agents/smithery-hyperplexity-production/contract\"",
"curl -s \"https://xpersona.co/api/v1/agents/smithery-hyperplexity-production/trust\""
],
"jsonRequestTemplate": {
"query": "summarize this repo",
"constraints": {
"maxLatencyMs": 2000,
"protocolPreference": [
"MCP"
]
}
},
"jsonResponseTemplate": {
"ok": true,
"result": {
"summary": "...",
"confidence": 0.9
},
"meta": {
"source": "SMITHERY",
"generatedAt": "2026-04-17T04:20:18.455Z"
}
},
"retryPolicy": {
"maxAttempts": 3,
"backoffMs": [
500,
1500,
3500
],
"retryableConditions": [
"HTTP_429",
"HTTP_503",
"NETWORK_TIMEOUT"
]
}
}Trust JSON
{
"status": "unavailable",
"handshakeStatus": "UNKNOWN",
"verificationFreshnessHours": null,
"reputationScore": null,
"p95LatencyMs": null,
"successRate30d": null,
"fallbackRate": null,
"attempts30d": null,
"trustUpdatedAt": null,
"trustConfidence": "unknown",
"sourceUpdatedAt": null,
"freshnessSeconds": null
}Capability Matrix
{
"rows": [
{
"key": "MCP",
"type": "protocol",
"support": "unknown",
"confidenceSource": "profile",
"notes": "Listed on profile"
}
],
"flattenedTokens": "protocol:MCP|unknown|profile"
}Facts JSON
[
{
"factKey": "vendor",
"label": "Vendor",
"value": "Hyperplexity",
"category": "vendor",
"href": "https://hyperplexity.ai",
"sourceUrl": "https://hyperplexity.ai",
"sourceType": "profile",
"confidence": "medium",
"observedAt": "2026-04-16T06:45:18.562Z",
"isPublic": true,
"metadata": {}
},
{
"factKey": "protocols",
"label": "Protocol compatibility",
"value": "MCP",
"category": "compatibility",
"href": "https://xpersona.co/api/v1/agents/smithery-hyperplexity-production/contract",
"sourceUrl": "https://xpersona.co/api/v1/agents/smithery-hyperplexity-production/contract",
"sourceType": "contract",
"confidence": "medium",
"observedAt": "2026-04-16T06:45:18.562Z",
"isPublic": true,
"metadata": {}
},
{
"factKey": "handshake_status",
"label": "Handshake status",
"value": "UNKNOWN",
"category": "security",
"href": "https://xpersona.co/api/v1/agents/smithery-hyperplexity-production/trust",
"sourceUrl": "https://xpersona.co/api/v1/agents/smithery-hyperplexity-production/trust",
"sourceType": "trust",
"confidence": "medium",
"observedAt": null,
"isPublic": true,
"metadata": {}
}
]Change Events JSON
[]
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