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Glama

cypher-mcp

by io.github.lonniev

cypher_upsert_pull_request

Upsert the live state of a GitHub PR into the graph.

Input Schema

TableJSON Schema
NameRequiredDescriptionDefault
urlYesThe PR's canonical GitHub URL.
npubNo
draftNoTrue while the PR is a draft (in-progress, not yet up for review).
stateYesLifecycle state: 'open' | 'closed' (merged PRs are closed with merged_at set).
titleYesPR title.
authorNoGitHub login that opened the PR.
numberYesThe PR number (node identity).
base_refNoBase branch the PR targets (e.g. 'main').
head_refNoHead branch of the PR (e.g. 'agent/fix-123').
head_shaNoHead commit SHA (changes on each synchronize).
merged_atNoGitHub merge timestamp (ISO-8601), or null if not merged.
repo_nameYesRepository name.
created_atNoGitHub creation timestamp (ISO-8601); a graph timestamp is used if omitted.
dpop_tokenNo

Schema Changelog

Changes observed during successful MCP inspections. Dates show when Glama detected each change.

  1. Added
  2. Removed
  3. Added
  4. Removed
  5. Added
  6. Removed
  7. Added

TDQS

C2.8/5.0
Behavior2/5

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

With no annotations provided, the description carries the full burden of behavioral disclosure. It only states 'Upsert' (implying insert-or-update) but fails to explain idempotency, whether partial updates are allowed, what 'the graph' refers to, authentication requirements, or side effects on existing data. This is insufficient for a tool with 14 parameters.

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

Conciseness3/5

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

The description is extremely concise (one sentence, 8 words), but at the expense of necessary detail. It earns its place by stating the core purpose, yet for a 14-parameter tool with no annotations or output schema, it is under-specified – sacrificing completeness for brevity.

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

Completeness2/5

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

Given the tool's complexity (14 parameters, no output schema, no annotations), the description is too sparse to enable correct invocation. It omits critical context such as identity semantics (e.g., `number`+`repo_name` as composite key), scope of 'live state', and expected return behavior, making it incomplete for reliable use.

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

Parameters3/5

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

Schema description coverage is 86%, so the input schema already documents most parameters well. The description adds no parameter-level or usage context beyond what the schema provides, but given high coverage, baseline score 3 is appropriate.

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

Purpose4/5

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

The description clearly states the action ('Upsert') and the resource ('live state of a GitHub PR into the graph'), making the tool's primary function unmistakable. It distinguishes from sibling tools like `cypher_list_pull_requests` (read-only list) or `cypher_pr_provenance` (provenance query), though it does not explicitly name alternatives.

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

Usage Guidelines2/5

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

The description offers no guidance on when to use this tool versus other PR-related siblings (e.g., `cypher_link_pr`, `cypher_list_pull_requests`). There is no mention of prerequisites, exclusions, or typical use cases, leaving the agent to infer appropriateness solely from the name.

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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TDQS

C2.7/5.0
Disambiguation2/5

The set is heavily clustered: audit_why_exists, explain_capability, suggest_capability_why, and authorize_capability_why all answer the same basic 'why does this capability exist?' question and differ mainly in provenance/authority. Many status and provenance tools (adoption_status, session_status, service_status, issue_provenance, pr_provenance, symbol_provenance, service_provenance) also blur together without close reading.

Naming Consistency4/5

The overwhelming majority of tools follow a predictable cypher_verb_noun pattern in snake_case, which provides strong naming consistency across a very large surface. Minor deviations such as cypher_oracle_about, cypher_oracle_how_to_join, cypher_which_service_handles, and cypher_what_realizes_capability are noticeable but do not break the overall pattern.

Tool Count1/5

112 tools is an extreme count for a single MCP server, regardless of how well the clusters are named; it heavily burdens tool selection, context, and agent discovery. The set spans unrelated domains including payments, coupons, credentials, provenance, issues, patents, queries, pricing, and NOS transformations, which should be split into separate focused servers.

Completeness4/5

Many domain clusters have strong lifeycle coverage: COUPs have mint/list/update/delete/redeem, credentials have courier delivery/box status/update/delete/forget, and the named-query catalog has full CRUD plus published-tool management. Minor gaps exist—e.g., no generic list_services, no delete for capabilities, and no close/resolve action for issues—but most flows have no outright dead end.

Resources