Scholar Feed MCP Server

Find Research Gaps

find_gaps

Read-only

Identify missing canonical and novel research papers for any collection or topic by analyzing gaps between your library and the field's foundational anchors and recent high-novelty work.

Instructions

Find important work you HAVEN'T saved, for a collection or topic — a 'what am I missing?' analysis. Returns two buckets: foundational_gaps (canonical citation-graph anchors in the niche, not in your library) and frontier_gaps (recent high-novelty work in the niche, not yet saved). Provide exactly one seed: collection_name OR collection_id OR topic. The backend derives the niche, runs lineage + recent-novelty search, and subtracts your saved set. Read-only. Requires SF_API_KEY (it needs your library to subtract) and is a Pro feature — free accounts receive an upgrade prompt.

Input Schema

TableJSON Schema

Name	Required	Description	Default
`collection_name`	No	Analyze gaps for a collection by name (resolved by the backend). Provide exactly one seed.
`collection_id`	No	Analyze gaps for a collection by UUID. Provide exactly one seed.
`topic`	No	Analyze gaps for a free-text topic/area. Provide exactly one seed.
`scope`	No	Which gaps to surface: 'foundational' (canonical anchors you're missing), 'frontier' (recent novel work you haven't saved), or 'both' (default).	both
`limit`	No	Max gaps per bucket (max 50). Default 10.

Output Schema

TableJSON Schema

Name	Required	Description
`foundational_gaps`	No	Canonical anchors in the niche not in your library.
`frontier_gaps`	No	Recent high-novelty work you haven't saved.
`ok`	No
`message`	No

Schema Changelog

Changes observed during successful MCP inspections.

Changed1 schema field changedv3.8.0Jun 9, 2026

changedOutput schema / (root)

Previous value: -nullNew value: +{
+  "$schema": "http://json-schema.org/draft-07/schema#",
+  "additionalProperties": false,
+  "properties": {
+    "foundational_gaps": {
+      "description": "Canonical anchors in the niche not in your library.",
+      "items": {
+        "additionalProperties": {},
+        "description": "A paper record. Verbose calls add extraction fields (method_name, datasets, baselines, ...).",
+        "properties": {
+          "arxiv_id": {
+            "type": "string"
+          },
+          "arxiv_url": {
+            "type": "string"
+          },
+          "authors": {
+            "items": {
+              "type": "string"
+            },
+            "type": "array"
+          },
+          "categories": {
+            "items": {
+              "type": "string"
+            },
+            "type": "array"
+          },
+          "citation_count": {
+            "type": "number"
+          },
+          "github_stars": {
+            "anyOf": [
+              {
+                "type": "number"
+              },
+              {
+                "type": "null"
+              }
+            ]
+          },
+          "github_url": {
+            "anyOf": [
+              {
+                "type": "string"
+              },
+              {
+                "type": "null"
+              }
+            ]
+          },
+          "has_code": {
+            "type": "boolean"
+          },
+          "impact_pct": {
+            "anyOf": [
+              {
+                "type": "number"
+              },
+              {
+                "type": "null"
+              }
+            ]
+          },
+          "impact_tier": {
+            "anyOf": [
+              {
+                "type": "string"
+              },
+              {
+                "type": "null"
+              }
+            ]
+          },
+          "institution_tags": {
+            "items": {
+              "type": "string"
+            },
+            "type": "array"
+          },
+          "llm_novelty_score": {
+            "anyOf": [
+              {
+                "type": "number"
+              },
+              {
+                "type": "null"
+              }
+            ]
+          },
+          "llm_significance": {
+            "anyOf": [
+              {
+                "type": "string"
+              },
+              {
+                "type": "null"
+              }
+            ]
+          },
+          "llm_summary": {
+            "anyOf": [
+              {
+                "type": "string"
+              },
+              {
+                "type": "null"
+              }
+            ]
+          },
+          "pdf_url": {
+            "type": "string"
+          },
+          "primary_category": {
+            "type": "string"
+          },
+          "published_date": {
+            "type": "string"
+          },
+          "rank_score": {
+            "type": "number"
+          },
+          "similarity": {
+            "type": "number"
+          },
+          "title": {
+            "type": "string"
+          },
+          "venue_name": {
+            "anyOf": [
+              {
+                "type": "string"
+              },
+              {
+                "type": "null"
+              }
+            ]
+          },
+          "year": {
+            "type": "number"
+          }
+        },
+        "type": "object"
+      },
+      "type": "array"
+    },
+    "frontier_gaps": {
+      "description": "Recent high-novelty work you haven't saved.",
+      "items": {
+        "additionalProperties": {},
+        "description": "A paper record. Verbose calls add extraction fields (method_name, datasets, baselines, ...).",
+        "properties": {
+          "arxiv_id": {
+            "type": "string"
+          },
+          "arxiv_url": {
+            "type": "string"
+          },
+          "authors": {
+            "items": {
+              "type": "string"
+            },
+            "type": "array"
+          },
+          "categories": {
+            "items": {
+              "type": "string"
+            },
+            "type": "array"
+          },
+          "citation_count": {
+            "type": "number"
+          },
+          "github_stars": {
+            "anyOf": [
+              {
+                "type": "number"
+              },
+              {
+                "type": "null"
+              }
+            ]
+          },
+          "github_url": {
+            "anyOf": [
+              {
+                "type": "string"
+              },
+              {
+                "type": "null"
+              }
+            ]
+          },
+          "has_code": {
+            "type": "boolean"
+          },
+          "impact_pct": {
+            "anyOf": [
+              {
+                "type": "number"
+              },
+              {
+                "type": "null"
+              }
+            ]
+          },
+          "impact_tier": {
+            "anyOf": [
+              {
+                "type": "string"
+              },
+              {
+                "type": "null"
+              }
+            ]
+          },
+          "institution_tags": {
+            "items": {
+              "type": "string"
+            },
+            "type": "array"
+          },
+          "llm_novelty_score": {
+            "anyOf": [
+              {
+                "type": "number"
+              },
+              {
+                "type": "null"
+              }
+            ]
+          },
+          "llm_significance": {
+            "anyOf": [
+              {
+                "type": "string"
+              },
+              {
+                "type": "null"
+              }
+            ]
+          },
+          "llm_summary": {
+            "anyOf": [
+              {
+                "type": "string"
+              },
+              {
+                "type": "null"
+              }
+            ]
+          },
+          "pdf_url": {
+            "type": "string"
+          },
+          "primary_category": {
+            "type": "string"
+          },
+          "published_date": {
+            "type": "string"
+          },
+          "rank_score": {
+            "type": "number"
+          },
+          "similarity": {
+            "type": "number"
+          },
+          "title": {
+            "type": "string"
+          },
+          "venue_name": {
+            "anyOf": [
+              {
+                "type": "string"
+              },
+              {
+                "type": "null"
+              }
+            ]
+          },
+          "year": {
+            "type": "number"
+          }
+        },
+        "type": "object"
+      },
+      "type": "array"
+    },
+    "message": {
+      "type": "string"
+    },
+    "ok": {
+      "type": "boolean"
+    }
+  },
+  "type": "object"
+}

Addedv3.7.0Jun 4, 2026

TDQS

A4.6/5.0

Behavior5/5

Does the description disclose side effects, auth requirements, rate limits, or destructive behavior?

Annotations declare readOnlyHint=true and destructiveHint=false, and the description reinforces 'Read-only.' It explains the backend process: 'derives the niche, runs lineage + recent-novelty search, subtracts your saved set.' No contradictions, and additional context (API key requirement, Pro feature) is provided.

Agents need to know what a tool does to the world before calling it. Descriptions should go beyond structured annotations to explain consequences.

Conciseness5/5

Is the description appropriately sized, front-loaded, and free of redundancy?

Five well-structured sentences front-load the purpose and then detail usage. Every sentence adds essential information; no unnecessary words or repetition.

Shorter descriptions cost fewer tokens and are easier for agents to parse. Every sentence should earn its place.

Completeness4/5

Given the tool's complexity, does the description cover enough for an agent to succeed on first attempt?

Given the tool has 5 parameters (none required), high schema coverage, and an output schema exists, the description covers the key behavioral aspects: seed specification, scope, limit, API key requirement, and Pro feature. Slight deduction for not mentioning the output schema explicitly, but the description is still complete enough for correct tool use.

Complex tools with many parameters or behaviors need more documentation. Simple tools need less. This dimension scales expectations accordingly.

Parameters4/5

Does the description clarify parameter syntax, constraints, interactions, or defaults beyond what the schema provides?

Schema coverage is 100%, so baseline is 3. The description adds value by explaining mutual exclusivity of seed parameters ('Provide exactly one seed') and clarifying the scope enum values ('foundational,' 'frontier,' 'both'). This goes beyond the schema's minimal descriptions.

Input schemas describe structure but not intent. Descriptions should explain non-obvious parameter relationships and valid value ranges.

Purpose5/5

Does the description clearly state what the tool does and how it differs from similar tools?

The description clearly states the tool's purpose: 'Find important work you HAVEN'T saved, for a collection or topic — a 'what am I missing?' analysis.' It precisely identifies the two output buckets (foundational_gaps and frontier_gaps) and distinguishes this tool from siblings like search_papers or list_library by focusing on missing works.

Agents choose between tools based on descriptions. A clear purpose with a specific verb and resource helps agents select the right tool.

Usage Guidelines4/5

Does the description explain when to use this tool, when not to, or what alternatives exist?

Provides explicit usage constraints: 'Provide exactly one seed: collection_name OR collection_id OR topic.' It mentions the need for SF_API_KEY and that it's a Pro feature. While it doesn't explicitly state when not to use it or list alternatives, the guidance is clear and actionable.

Agents often have multiple tools that could apply. Explicit usage guidance like "use X instead of Y when Z" prevents misuse.