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Teradata

Teradata MCP Server

Official
by Teradata

graph_analyseDatabase

Executes four graph analyses (root objects, connected components, cycles, and BFS waves) in a single call with shared edge fetch to assess database migration readiness.

Instructions

Composite graph analysis — runs findRootObjects, connectedComponents, detectCycles, and bfsLevels in a single MCP call with ONE shared edge fetch.

This tool eliminates the scalability bottleneck of serial MCP round- trips by combining four graph analyses that would otherwise require four separate tool calls, each independently fetching the same edge set from Teradata.

Performance vs individual tools:

  • 1 SQL round-trip instead of 4 (shared edge fetch)

  • 1 MCP response instead of 4 (eliminates stdio serialisation overhead)

  • Same algorithmic complexity (O(V+E) BFS, O(α·N) Union-Find, O(V+E) DFS)

  • In-memory edge sharing: all analyses operate on the same Python list

Use this for:

  • Full database migration readiness assessment

  • Pre-migration cycle + root + wave analysis in one call

  • Dashboard data population (all four analyses needed simultaneously)

  • Any workflow that would otherwise call 3+ individual graph tools

Arguments: container_pattern - str: CSV LIKE patterns for container scope. Supports wildcards (%) and CSV format. Examples: '%SALES%', '%SALES%,%FINANCE%', 'PROD_%'

                  CRITICAL: STRING type, not array.
                  CORRECT: container_pattern="%SALES%,%FINANCE%"
                  WRONG:   container_pattern=["%SALES%", "%FINANCE%"]

exclude_objects - str: CSV LIKE patterns to exclude. Default: '' (no exclusions)

top_n_roots - int: Number of top root objects (by downstream dependent count) to include in BFS wave analysis. Default: 4

max_depth_down - int: Maximum downstream BFS hops from roots. Default: 10

max_depth_up - int: Maximum upstream BFS hops from roots. 0 = skip upstream analysis. Default: 0

edge_repository - str: Edge repository view/table conforming to the Graph Edge Contract (Src_Container_Name, Src_Object_Name, Src_Kind, Tgt_Container_Name, Tgt_Object_Name, Tgt_Kind columns). Call graph_edgeContractDDL to generate one. Required parameter — no default.

Returns: ResponseType: single response containing all four analyses:

{ "root_objects": { "objects": [...], "summary": {...} }, "components": { "node_details": [...], "summaries": [...], "stats": [...] }, "cycles": { "details": [...], "summaries": [...], "stats": [...] }, "bfs_waves": { "nodes": [...], "cycle_candidates": [...], "summary": {...} }, "edge_stats": { "total_edges": N, "fetch_time_ms": N } }

Example calls:

Full analysis of Sales and Finance databases

handle_graph_analyseDatabase( conn=connection, container_pattern="%SALES%,%FINANCE%", edge_repository="MY_LINEAGE_DB.EdgeRepository" )

Single database family with top 8 roots

handle_graph_analyseDatabase( conn=connection, container_pattern="%FINANCE%", top_n_roots=8, edge_repository="MY_LINEAGE_DB.EdgeRepository" )

Exclude sandbox schemas

handle_graph_analyseDatabase( conn=connection, container_pattern="PROD_%,STAGE_%", exclude_objects="SANDBOX%,%.temp_%", edge_repository="MY_LINEAGE_DB.EdgeRepository" )

Input Schema

TableJSON Schema
NameRequiredDescriptionDefault
container_patternYes
exclude_objectsNo
top_n_rootsNo
max_depth_downNo
max_depth_upNo
edge_repositoryNo
Behavior4/5

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

No annotations provided, so description carries full burden. It explains performance characteristics, in-memory edge sharing, and that it eliminates serial round-trips. Could explicitly state it's non-mutating, but implied by 'analysis' nature.

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?

Description is lengthy but well-structured with sections: intro, performance, use cases, arguments, returns, examples. Front-loaded with purpose. Minor redundancy in performance comparison could be tightened.

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?

Given no output schema, description includes full return structure with example JSON. Covers all parameters with examples and edge cases. Complete for a composite tool with no missing gaps.

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

Parameters5/5

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

Schema coverage is 0%, but description provides detailed parameter descriptions, including types, defaults, examples, and critical notes (e.g., container_pattern must be string not array). Fully compensates for missing schema documentation.

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?

Description clearly states it's a composite graph analysis tool that runs findRootObjects, connectedComponents, detectCycles, and bfsLevels in a single call. Distinguishes from individual sibling tools by highlighting performance benefits of combined execution and shared edge fetch.

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

Usage Guidelines5/5

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

Explicitly lists use cases: full migration readiness, pre-migration analysis, dashboard population, any workflow requiring 3+ individual calls. Implicitly suggests not to use when only one analysis is needed, though not strongly stated.

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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