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Python
Remote

ebi-pdbe-graph_node_relationships

Read-onlyIdempotent

Verifies PDBe graph node labels and returns their incoming, outgoing, and self-loop relationships so you can confirm schema directions before writing Cypher queries.

Instructions

Verifies one or more PDBe graph node labels and returns the relationships connected to each label.
Use this tool after inspecting the node and edge schema, when you have selected node labels for a Cypher query
and want to confirm that the labels and relationship directions exist in the PDBe graph schema.

For each requested node label, this tool returns:
- Whether the node label exists in the schema
- Outgoing relationship patterns from that node label
- Incoming relationship patterns to that node label
- Self-loop relationship patterns where both ends use the same node label
- A bidirectional note when the schema has the same relationship label in both directions between two node labels

Parameters:
    node_labels (required): A list of exact, case-sensitive node labels to verify.
        Example: ["Entry", "Entity", "UniProt"]

Expected Output Format (text):
Node: Entry
Status: Found
Outgoing edges:
  - (Entry)-[:HAS_ENTITY]->(Entity)
Incoming edges:
  - None
Self-loop edges:
  - None

Node: FakeNode
Status: Not found in schema

Input Schema

NameRequiredDescriptionDefault
node_labelsYesExact, case-sensitive node labels to verify against the PDBe graph schema.

Schema Changelog

Changes observed during successful MCP inspections.

  1. Addedv2.0.1

TDQS

A4.6/5.0
Behavior5/5

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

Annotations already declare readOnlyHint, idempotentHint, and destructiveHint=false, and the description still adds substantial behavior: per-label existence status, outgoing, incoming and self-loop pattern buckets, and a bidirectional note when the same relationship label appears in both directions. It even supplies a text output template, which is essential because there is no output schema.

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

Conciseness4/5

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

It is front-loaded with purpose and usage before enumerating return fields, and the bulleted structure plus fenced example makes the output contract scannable. The expected-output block is longer than strictly necessary, but it compensates for the absent output schema, so the length is largely justified.

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

Completeness5/5

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

With one parameter, no output schema, and simple read-only annotations, this description covers everything an agent needs: when to call it, exact label casing requirements, and the full shape of the response including the not-found case. No gaps remain that would cause a misinvocation.

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% and the parameter already documents exact, case-sensitive matching, so the baseline is a 3. The description earns an extra point by adding concrete example values (["Entry", "Entity", "UniProt"]) and confirming the input is a list processed per label, which clarifies expected cardinality and naming style.

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 first sentence names a specific verb and resource: verifies PDBe graph node labels and returns relationships connected to each label. That is clearly distinguishable from siblings like graph_nodes and graph_edges, which list schema elements rather than resolving label-to-label relationship patterns.

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?

The description states the timing and intent explicitly: use it after inspecting the node and edge schema, once node labels have been chosen for a Cypher query, to confirm labels and relationship directions exist. It does not name graph_nodes or graph_edges as the specific alternative tools, so the routing is implied rather than spelled out.

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

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