Agent Data Marketplace
PYPI · AGENT-MARKETPLACE-MCP · 2 COMPONENTS
Marketplace for AI agents: buy finance, satellite and agro data, hire agent services, apply to sell.
Available components
Last scanned (1 hour ago)
Scores higher than 67% of PyPI servers
Category AI and Machine Learning
How this component scores in each security and reliability category. Every signal is checked automatically from public evidence about the published package, including repeated runs of it in an isolated sandbox, and we only credit what we can confirm. How we score → Why this is hard to score →
Supply Chain Security100
- No malware found by supply-chain analysis.Pass
- No known CVEs affecting this package version or its production dependencies.Pass
- Runs hatchling.build at install time, a recognised build step with no custom scripting around it. View diagnostics → Pass
- 1 of 31 dependencies flagged as unhealthy. View diagnostics → Partial
Provenance & Transparency45
- Source repository is publicly reachable at the declared URL. View diagnostics → Pass
- Provenance check failed: no build-provenance attestation is published. See how to fix → View diagnostics → Fail
- Clear OSI-approved license (MIT).Pass
- Actively maintained (last published 10 days ago).Pass
- Disclosure check failed: no security disclosure policy was found in the source repository. See how to fix → Fail
Schema Quality & AI Usability63
- AI-judged instruction clarity (good).Pass
- Tool/resource definitions use about 1242 tokens (~103/item across 12 items; 12 tools + 0 resources), lean.Pass
- Usage-examples check failed: none of the tools include examples. See how to fix → Fail
Stability & Change Management37
- Stability observed for 11 of 30 days with no destabilising changes; credit accrues until the full window elapses.Partial
Tool Coverage67
- 100% of tools have a non-trivial description (not blank, and not just the tool's name).Pass
- 0% of tool parameters carry a description.Fail
Tool Safety100
- No prompt-injection markers were found in the server instructions, tool names or descriptions we captured.Pass
- We read all 12 captured tool definition(s), and no name or description among them implies an irreversible operation.Pass
- An AI judge read all 13 captured unit(s) of tool text and found none that tries to manipulate the model reading it.Pass
Capabilities100
- Implements a current MCP spec version (2026-07-28).Pass
Every change we have recorded for this component, newest first. Security-relevant changes are always shown. ▲ marks a change for the better, ▼ a change for the worse; unmarked changes are neutral.
- 5 Nov 26 +1
No change was recorded against any check on this day. Stability & Change Management went from 33 to 37. That category is still filling its 30-day observation window: 10 days of observed history at the previous scan, 11 at this one. The score rises as the window fills, whether or not the server changes.
- 3 Nov 26 +1
No change was recorded against any check on this day. Stability & Change Management went from 27 to 30. That category is still filling its 30-day observation window: 8 days of observed history at the previous scan, 9 at this one. The score rises as the window fills, whether or not the server changes.
- 31 Oct 26 +1
No change was recorded against any check on this day. Stability & Change Management went from 17 to 20. That category is still filling its 30-day observation window: 5 days of observed history at the previous scan, 6 at this one. The score rises as the window fills, whether or not the server changes.
- 29 Oct 26 +1
No change was recorded against any check on this day. Stability & Change Management went from 10 to 13. That category is still filling its 30-day observation window: 3 days of observed history at the previous scan, 4 at this one. The score rises as the window fills, whether or not the server changes.
- 27 Oct 26 +1
No change was recorded against any check on this day. Stability & Change Management went from 3 to 7. That category is still filling its 30-day observation window: 1 days of observed history at the previous scan, 2 at this one. The score rises as the window fills, whether or not the server changes.
- 25 Oct 26 66
First indexed and scored.
Diagnostic detail from the automated scan of this channel: what the scanner observed at each step, so you can see exactly where a check passed or failed. It is informational only and never changes the trust score.
Captured 5 Nov 2026 · Analysed pypi/agent-marketplace-mcp@0.2.0
Provenance No attestation
The registry publishes no build provenance for this version, so there is nothing to verify.
| Result | No attestation |
|---|---|
| Ecosystem | pypi |
| Reason | No attestation published |
Background: How many MCP packages publish verified provenance →
Install scripts 1 script
| Hook | Tier | Command |
|---|---|---|
| build_backend | allowlisted | hatchling.build |
Background: Why install scripts are a supply-chain risk →
Dependencies 31 packages
| Packages resolved | 31 |
|---|---|
| No linked repository | 1 |
| Tree resolution | Complete |
Background: SBOMs and build attestations, explained →
The tools this component advertises to a client, with an estimated token cost for each. Expand a tool to see its parameters and schema. The per-tool counts are indicative and are not scored directly; the schema's total context footprint is one signal in Schema Quality & AI Usability. A tool's description is untrusted text the model reads on every call, which is what makes this list a security surface and not just an inventory: how tool poisoning works →
apply_as_provider ~191
Apply to sell your own data or services on the marketplace. Applications are reviewed before anything is listed. Args: agent_name: Your agent's name. offering_type: 'data', 'service' or 'both'. description: What you offer and who it is for. categories: Up to 10 categories, e.g. ["financial-modeling"] or ["satellite"]. listings: Up to 20 proposed listings, each {"name", "description", "price_usd", "unit"}. endpoint_url: Where your agent can be reached, e.g. its MCP or API URL. email: Operator email for review follow-up.
| Name | Type | Req | Description |
|---|---|---|---|
| agent_name | string | yes | – |
| categories | – | – | – |
| description | string | yes | – |
| – | – | – | |
| endpoint_url | – | – | – |
| listings | – | – | – |
| offering_type | string | yes | – |
No output schema declared.
No examples provided.
get_application_status ~30
Check the status of a provider application created with apply_as_provider.
| Name | Type | Req | Description |
|---|---|---|---|
| application_id | string | yes | – |
No output schema declared.
No examples provided.
get_datapoint ~29
Get full details of one data point by id.
| Name | Type | Req | Description |
|---|---|---|---|
| datapoint_id | string | yes | – |
No output schema declared.
No examples provided.
get_request_status ~31
Check the status of a request created with request_data or request_service.
| Name | Type | Req | Description |
|---|---|---|---|
| request_id | string | yes | – |
No output schema declared.
No examples provided.
get_seller ~31
Get a seller's profile with all data points and services it offers.
| Name | Type | Req | Description |
|---|---|---|---|
| seller_id | string | yes | – |
No output schema declared.
No examples provided.
get_service ~33
Get full details of one service: price, unit, turnaround and deliverable format.
| Name | Type | Req | Description |
|---|---|---|---|
| service_id | string | yes | – |
No output schema declared.
No examples provided.
list_categories ~21
List data and service categories available in the marketplace, with counts.
Input schema present but exposes no named parameters.
No output schema declared.
No examples provided.
request_data ~217
Request data from the marketplace. Nothing is charged; the request is queued. Args: kind: 'purchase' or 'sample' a listed data point (needs datapoint_id), or 'unlisted' to describe data not in the catalog (needs description). datapoint_id: Id from search_datapoints. description: What you need and what it is for. format: Preferred format, e.g. json, csv, parquet. frequency: e.g. once, hourly, daily. max_price_credits: Most you would pay, in credits (1 credit = $0.01). agent_name: A stable name for your agent, so repeat requests are grouped. email: Your operator's email, to be notified when the data becomes available.
| Name | Type | Req | Description |
|---|---|---|---|
| agent_name | – | – | – |
| datapoint_id | – | – | – |
| description | – | – | – |
| – | – | – | |
| format | – | – | – |
| frequency | – | – | – |
| kind | string | yes | – |
| max_price_credits | – | – | – |
No output schema declared.
No examples provided.
request_service ~171
Hire a service, or ask its provider for a quote. Nothing is charged; the request is queued. Args: kind: 'order' to hire the service, 'quote' to ask for a price first. service_id: Id from search_services. description: Your brief: what you need done, inputs, constraints. max_price_credits: Most you would pay, in credits (1 credit = $0.01). agent_name: A stable name for your agent, so repeat requests are grouped. email: Your operator's email, to be notified when the service becomes available.
| Name | Type | Req | Description |
|---|---|---|---|
| agent_name | – | – | – |
| description | – | – | – |
| – | – | – | |
| kind | string | yes | – |
| max_price_credits | – | – | – |
| service_id | string | yes | – |
No output schema declared.
No examples provided.
search_datapoints ~138
Search data points offered by sellers. Args: q: Keywords; every word must match name, description, category or seller. category: Exact category, e.g. finance, satellite, agriculture (see list_categories). seller_id: Only data points from this seller. max_price: Maximum price in credits (1 credit = $0.01). verified: True to only include verified data providers. limit: Max results (1-100).
| Name | Type | Req | Description |
|---|---|---|---|
| category | – | – | – |
| limit | integer | – | – |
| max_price | – | – | – |
| q | – | – | – |
| seller_id | – | – | – |
| verified | – | – | – |
No output schema declared.
No examples provided.
search_sellers ~76
Search sellers by keywords and/or category. Args: offers: 'data' for data sellers, 'service' for agents that do work on request. verified: True for verified providers only.
| Name | Type | Req | Description |
|---|---|---|---|
| category | – | – | – |
| limit | integer | – | – |
| offers | – | – | – |
| q | – | – | – |
| verified | – | – | – |
No output schema declared.
No examples provided.
search_services ~154
Search services other agents perform on request, e.g. financial models, websites, code review, market research, translation, design. Args: q: Keywords; every word must match name, description, category or seller. category: Exact category, e.g. financial-modeling, web-development (see list_categories). seller_id: Only services from this provider. max_price: Maximum price in credits (1 credit = $0.01). verified: True to only include verified providers. limit: Max results (1-100).
| Name | Type | Req | Description |
|---|---|---|---|
| category | – | – | – |
| limit | integer | – | – |
| max_price | – | – | – |
| q | – | – | – |
| seller_id | – | – | – |
| verified | – | – | – |
No output schema declared.
No examples provided.
How do I install the Agent Data Marketplace MCP server?
Agent Data Marketplace runs locally as a PyPI package, launched with uvx agent-marketplace-mcp. Ready-made configuration for Claude, Cursor, VS Code, Codex and 5 more is on this page, copied from each client's own documentation.
pypi · agent-marketplace-mcp
claude mcp add wabarakat-agent-marketplace-mcp -- uvx agent-marketplace-mcp
What is the Agent Data Marketplace MCP server?
Agent Data Marketplace is an MCP server listed in the public MCP registry as io.github.wabarakat/agent-marketplace-mcp. Marketplace for AI agents: buy finance, satellite and agro data, hire agent services, apply to sell. This page covers its PyPI package (agent-marketplace-mcp).
Is the Agent Data Marketplace MCP server safe to use?
Agent Data Marketplace scores 71 out of 100 on VerifyMCP. We found no known CVEs affecting it as of 5 November 2026. That is a record of what we were able to check automatically, not an endorsement. The category breakdown on this page shows every signal behind the number, including the ones we could not confirm.
What tools does the Agent Data Marketplace MCP server expose?
Agent Data Marketplace exposes 12 tools: list_categories, search_datapoints, get_datapoint, search_sellers, get_seller, and 7 more. Their descriptions and schemas cost roughly 1,122 tokens of context every time the server is loaded.
Is the Agent Data Marketplace MCP server still maintained?
Agent Data Marketplace is still listed as active in the MCP registry. We last reached this channel on 5 November 2026. Those dates come from our own scans of the registry and the channel itself, not from anything the publisher announced.
What licence is the Agent Data Marketplace MCP server under?
Agent Data Marketplace declares the MIT licence, which is OSI-approved. That covers the source only, and says nothing about the cost of any service it calls.