paper_fulltext_search
Search INSIDE the indexed open-access corpus (arXiv + PubMed Central OA full text) for a phrase or keywords and get back the matching passages, each with the paper title, authors, and a snippet around the match. This is the headline feature: agents can find where a finding or method is discussed ...
This record as markdown: /tools/io-github-blackboxfoundry-livedatalink/paper-fulltext-search.md
What paper_fulltext_search does on Livedatalink
AI agents call paper_fulltext_search to retrieve information from Livedatalink without modifying anything. It is typically the context-gathering step in research, monitoring, and reporting workflows, before the agent takes action elsewhere.
| Parameter | Type | Required | Description |
|---|---|---|---|
limit | number | — | Maximum passages to return (default 10, max 50). |
query | string | Yes | Phrase or keywords to find inside the papers, e.g. 'scaled dot-product attention', 'gradient checkpointing'. |
paper_key | string | — | Optional: restrict the search to a single indexed paper by its corpus key, e.g. 'arxiv:2310.12345'. |
Parameters from the server's own tool schema.
Why paper_fulltext_search is rated Low
Even though paper_fulltext_search only reads data, uncontrolled read access leaks sensitive information and racks up API costs: an agent caught in a retry loop can make thousands of calls a minute without anyone noticing.
Attacks that exploit this kind of access
The rule that runs paper_fulltext_search safely
PolicyLayer is an MCP gateway: it sits between your AI agents and Livedatalink, and checks every tool call against a rule you set before the call runs. Nothing changes on the server itself. For paper_fulltext_search, this is the rule to start with:
paper_fulltext_search is read-only, so it stays allowed. Everything else on the server is denied unless you say otherwise.
The button opens the PolicyLayer dashboard: create your workspace, connect Livedatalink, apply this rule, and every paper_fulltext_search call is checked against it from then on.
Questions about paper_fulltext_search
Search INSIDE the indexed open-access corpus (arXiv + PubMed Central OA full text) for a phrase or keywords and get back the matching passages, each with the paper title, authors, and a snippet around the match. This is the headline feature: agents can find where a finding or method is discussed across open-access papers. Optionally restrict to one paper by paper_key. It is categorised as a Read tool in the Livedatalink MCP Server, which means it retrieves data without modifying state.
paper_fulltext_search accepts 3 parameters: limit, query, paper_key. Required: query. The full parameter table on this page comes from the server's own tool schema.
Register the Livedatalink MCP server in PolicyLayer and add a rule for paper_fulltext_search: allow, deny, rate-limit, or require approval. Point your MCP client at the PolicyLayer proxy URL and the rule is enforced on every call, before it reaches Livedatalink. Nothing to install.
paper_fulltext_search is a Read tool with low risk. Read-only tools are generally safe to allow by default.
Yes. Add a rate_limit block to the paper_fulltext_search rule in your PolicyLayer policy. For example, setting max: 10 and window: 60 limits the tool to 10 calls per minute. Rate limits are tracked per agent session and reset automatically.
Set action: deny in the PolicyLayer policy for paper_fulltext_search. The AI agent will receive a policy violation error and cannot call the tool. You can also include a reason field to explain why the tool is blocked.
paper_fulltext_search is provided by the Livedatalink MCP server (https://livedatalink.ai/mcp). PolicyLayer sits as a proxy in front of this server to enforce policies before tool calls reach the server.
More on Livedatalink, and thousands of servers like it.
This server
Across the catalogue