SYS_TIME: 00:00:00.000 UTCGLOBAL_STATE: OPERATIONAL
Agentic Data Backbone

Your agents can't read the internet.
Vesper can.

Tell Vesper what you need - web pages, research papers, APIs, repos. It fetches, cleans, and delivers structured data your agent can actually use. No scrapers to maintain, no pipelines to babysit.

Begin Journey
$npx @vespermcp/setup@latest
// Telemetry
MEMORY_ALLOCATION
0 TB68% (12.4 TB_MAX)
PIPELINE_IO_STREAM
RAW_WEB_DATA
VESPER
SANITY_CHECKSPASS
SCHEMAS_LOCKED4,092
MCP_SERVERLISTENING
tty0 // execution_log
READONLY

// Script executed via MCP integration in Cursor
// Goal: Import, deduplicate, and vectorize raw HuggingFace dumps.

~vesper prepare --source hf:finance/q1 --tasks [clean,eval,export]
[0.00s] INIT Vesper pipeline v4.2
[0.12s] CONNECTING to HuggingFace (hf:finance/q1)
[0.65s] VFS_LOAD: Downloaded 1.2M rows (14.2 GB)
[1.04s] INITIATING evaluate_schema()...
WARN Row 4209: Null value in required field '"revenue"'
WARN Row 99120: Outlier detected in '"growth"' (Z-score > 5)
[2.10s] EXECUTING clean_heurstics()...
↳ Dropped 412 null rows.
↳ Capped 15 outliers via IQR method.
↳ Stripped heavy HTML from '"description"' bodies.
[3.40s] BINDING export format...
SUCCESSParquet output generated at ./data/finance_q1_clean.parquet

Automated Evaluation

Analyze multimodal quality, normalize ragged JSON schemas, and drop corrupted formats before your ingest breaks.

Multi-Source Fusion

Merge OpenML, Kaggle, S3, or HackerNews based on semantic exact/fuzzy heuristics without writing custom boilerplate.

MCP / Claude Native

The entire engine talks natively via the Model Context Protocol. Drop it into Cursor or Claude Desktop and let the AI find its own data.

Agent-Ready Formats

Export to Arrow, Parquet, or JSONL instantly. Optimized specifically for fast embedding generation and token-efficient RAG reading.

[ DEPLOYED_WORKFLOWS ]
01 // Active

Research & RAG

Collect papers, code, docs. Clean, dedup, export for retrieval agents.

Ready_to_deploy
02 // Active

Analytics & BI

S3, APIs, files → structured tables for analysis agents with zero manual extraction.

Ready_to_deploy
03 // Active

Compliance & Audit

Quality gates, provenance, telemetry for regulated dataset workflows.

Ready_to_deploy
I/O _ ENDPOINTSOMNICHANNEL
RESEARCH PAPERSSTATUS: NATIVE
WEB PAGESSTATUS: NATIVE
CODE & REPOSSTATUS: NATIVE
FILES & STORAGESTATUS: NATIVE
VIA_MCPLOCAL FILES
VIA_MCPPRIVATE APIS
VIA_MCPCUSTOM SOURCES
VIA_MCPDATABASES
[ VESPER_REST_API ]

Programmable Control

Call the Vesper API directly from your agent.
Point it at any source, define what to do with the data, and get structured results back.

POST/api/v1/pipeline/execute
{
  "source": "https://arxiv.org/search/?query=reinforcement+learning",
  "strategy": ["clean", "dedup", "structure"],
  "webhook_url": "https://agents.acme.com/ingest"
}
ASSET: VISUAL_DEMONSTRATION

Pricing

Simple plans for builders, teams, and enterprises running agentic data workflows.

Free
$0
For exploration
  • 500 API requests / month
  • 25 prepare runs / month
  • Public connectors only
  • Local lineage + local status
Start Free
Pro
$19
per user / month
$15/mo billed yearly
  • Unlimited requests + prepare runs
  • All connectors and advanced export
  • Web observability + lineage dashboard
  • Basic drift/staleness alerts
Upgrade to Pro
Enterprise
Custom
for teams and regulated orgs
  • SSO/SAML + RBAC
  • Private ingest / VPC options
  • Long retention + policy controls
  • SLA + dedicated onboarding
Contact Sales