digikey-mcp

by itsyashk

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Server Quality Checklist

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Latest release: v0.1.0
Disambiguation5/5
Each tool has a clearly distinct purpose: building BOMs, comparing candidates, exporting, fetching part details, refining BOMs, searching, and validating. No overlap or ambiguity.
Naming Consistency5/5
All tools follow a consistent `digikey_verb_noun` pattern with underscores, making the function of each tool immediately recognizable.
Tool Count5/5
7 tools is well-scoped for a BOM management and parts search server, covering key workflows without being excessive or minimal.
Completeness4/5
The tool set covers search, detail retrieval, BOM building, refining, comparing, validating, and exporting. Minor gap: no explicit delete or update of individual BOM lines, but refining handles changes.
Average 3.1/5 across 7 of 7 tools scored.
See the Tool Scores section below for per-tool breakdowns.
- No community issues in the last 6 months
- 12 commits in the last 12 weeks
- No stable releases found
- No critical vulnerability alerts
- No high-severity vulnerability alerts
- No code scanning findings
- CI is passing
This repository is licensed under Apache 2.0.
This repository includes a README.md file.
No tool usage detected in the last 30 days. Usage tracking helps demonstrate server value.
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How is the quality score calculated?

The overall quality score combines two components: Tool Definition Quality (70%) and Server Coherence (30%).

Tool Definition Quality measures how well each tool describes itself to AI agents. Every tool is scored 1–5 across six dimensions: Purpose Clarity (25%), Usage Guidelines (20%), Behavioral Transparency (20%), Parameter Semantics (15%), Conciseness & Structure (10%), and Contextual Completeness (10%). The server-level definition quality score is calculated as 60% mean TDQS + 40% minimum TDQS, so a single poorly described tool pulls the score down.

Server Coherence evaluates how well the tools work together as a set, scoring four dimensions equally: Disambiguation (can agents tell tools apart?), Naming Consistency, Tool Count Appropriateness, and Completeness (are there gaps in the tool surface?).

Tiers are derived from the overall score: A (≥3.5), B (≥3.0), C (≥2.0), D (≥1.0), F (<1.0). B and above is considered passing.

Tool Scores

Behavior2/5
Does the description disclose side effects, auth requirements, rate limits, or destructive behavior?
With no annotations, the description must disclose behavioral traits. It mentions saving a versioned bom.json and keeping custom items separate, but does not explain side effects like network access, auth requirements, or the effect of modes (offline/sandbox/production) from the schema. The description lacks detail on what happens when items are unresolved.
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?
The description is a single sentence that efficiently lists the tool's actions. It is not verbose, but could be more structured with bullet points or separate lines to improve readability. No unnecessary words.
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 complexity (13 parameters, nested objects) and the presence of an output schema, the description is insufficient. It does not specify how inputs like constraints, budget, or preferred_package are used. The output is mentioned briefly, but the overall behavior in relation to inputs is unclear.
Complex tools with many parameters or behaviors need more documentation. Simple tools need less. This dimension scales expectations accordingly.
Parameters1/5
Does the description clarify parameter syntax, constraints, interactions, or defaults beyond what the schema provides?
Schema description coverage is 0%, meaning the schema provides no parameter descriptions. The tool's description does not explain any of the 13 parameters, not even the required 'project_description'. This leaves the agent guessing about input semantics.
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 tool's purpose: planning architecture, building a requirement ledger, sourcing lines, and saving a BOM. However, it does not explicitly distinguish itself from sibling tools like digikey_refine_bom or digikey_validate_bom, which might perform similar tasks.
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?
No explicit guidance on when to use this tool versus alternatives. The description implies it is for building a BOM from scratch, but there is no mention of when not to use it or which sibling would be more appropriate.
Agents often have multiple tools that could apply. Explicit usage guidance like "use X instead of Y when Z" prevents misuse.
Behavior2/5
Does the description disclose side effects, auth requirements, rate limits, or destructive behavior?
With no annotations, the description must fully disclose behavior. It states the tool 'validates' and 'returns' results, implying a read-only operation, but does not clarify side effects (e.g., file saving via output_dir/saved_path) or whether it modifies state. The absence of such details reduces transparency.
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 a single sentence containing multiple validation aspects, which is concise but lacks structure. It could be split into clear sections (e.g., 'Validates... Returns...') to improve readability without adding length.
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?
The output schema covers return values, but the description fails to explain parameters, usage context, or behavioral traits. For a tool with 4 parameters and no annotations, this is insufficient for effective agent decision-making.
Complex tools with many parameters or behaviors need more documentation. Simple tools need less. This dimension scales expectations accordingly.
Parameters1/5
Does the description clarify parameter syntax, constraints, interactions, or defaults beyond what the schema provides?
Schema description coverage is 0%, and the description provides no information about parameters (bom, mode, output_dir, saved_path). All four parameters are undocumented, forcing the agent to infer their meaning from names alone. The description adds zero value beyond the schema.
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 uses specific verbs and resource: 'Validate BOM evidence, identifiers, freshness, duplicate lines, quantities, and engineering/interface consistency'. This clearly distinguishes it from sibling tools like digikey_build_electronics_bom (creation), digikey_compare_candidates (comparison), digikey_refine_bom (refinement), etc.
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 provides no guidance on when to use this tool versus alternatives. It does not mention prerequisites, context, or situations where another tool would be more appropriate. Users must infer usage from the name and description.
Agents often have multiple tools that could apply. Explicit usage guidance like "use X instead of Y when Z" prevents misuse.
Behavior3/5
Does the description disclose side effects, auth requirements, rate limits, or destructive behavior?
With no annotations, the description must carry the behavioral transparency burden. It states the tool 'show verified facts and trade-offs without claiming a user-dependent objective winner,' which is a useful behavioral constraint. However, it lacks details on whether the tool is read-only, requires authentication, or has side effects.
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?
The description is a single, concise sentence that is front-loaded with the core purpose. No extraneous words or redundant information.
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 complexity of the input schema (nested objects like Candidate, Evidence, Requirement) and the absence of parameter descriptions, the tool is inadequately specified for an AI agent to construct valid arguments. Output schema exists but does not compensate for missing input guidance.
Complex tools with many parameters or behaviors need more documentation. Simple tools need less. This dimension scales expectations accordingly.
Parameters1/5
Does the description clarify parameter syntax, constraints, interactions, or defaults beyond what the schema provides?
Input schema has 4 parameters (mode, candidates, identifiers, requirements) with 0% schema description coverage. The description provides no explanation of these parameters, their structure (e.g., how to specify candidates or requirements), or their relationship to each other. The agent cannot determine how to populate the arguments.
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 tool's action ('Compare candidate DKPNs against explicit requirements') and its output ('show verified facts and trade-offs'). It distinguishes itself from sibling tools (e.g., search, get details) by focusing on comparison. However, it does not explicitly differentiate from siblings.
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?
No guidance on when to use this tool versus alternatives (e.g., digikey_search_parts, digikey_get_part_details). There are no prerequisites, exclusions, or context indicating the appropriate scenario for using this comparison tool.
Agents often have multiple tools that could apply. Explicit usage guidance like "use X instead of Y when Z" prevents misuse.
Behavior3/5
Does the description disclose side effects, auth requirements, rate limits, or destructive behavior?
No annotations provided, so description carries full burden. 'Fetch' implies read-only behavior, and listed contents give some idea of expected output. However, missing details on authentication, rate limits, or error handling for invalid identifiers.
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 a single well-structured sentence that front-loads the tool's purpose and key outputs. However, it could be slightly expanded to cover parameter details without losing conciseness.
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?
Although the output schema may cover return values, the description is inadequate for the tool's complexity (3 parameters, one nested). It lacks parameter guidance and usage context, leaving gaps for the AI agent.
Complex tools with many parameters or behaviors need more documentation. Simple tools need less. This dimension scales expectations accordingly.
Parameters1/5
Does the description clarify parameter syntax, constraints, interactions, or defaults beyond what the schema provides?
Schema description coverage is 0%, and description does not explain any of the three parameters (identifier, quantity, requirements). It does not state that identifier expects a DKPN or MPN, nor does it describe quantity or the complex requirements object.
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 the tool fetches authoritative DigiKey product details for a DKPN or MPN, listing included data (pricing, availability, links, normalized parameters, evidence metadata). This distinguishes it from sibling tools like search or comparison tools.
Agents choose between tools based on descriptions. A clear purpose with a specific verb and resource helps agents select the right tool.
Usage Guidelines3/5
Does the description explain when to use this tool, when not to, or what alternatives exist?
Description implies usage context (when you need detailed product info for a specific identifier) but does not explicitly state when not to use or mention alternatives. Sibling tools are listed but not compared.
Agents often have multiple tools that could apply. Explicit usage guidance like "use X instead of Y when Z" prevents misuse.
Behavior2/5
Does the description disclose side effects, auth requirements, rate limits, or destructive behavior?
No annotations are provided, so the description must disclose behavioral traits. It mentions default filtering and that POSSIBLE_MATCH is 'unsafe', but lacks detail on side effects, authentication needs, rate limits, or what happens to the data. The source of the lines is also unclear.
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?
The description is concise at two sentences, front-loading the key behavior and format options. It is easy to parse, though could benefit from a brief note on the bom parameter.
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 complexity of the tool (6 parameters) and missing annotations, the description is insufficient. It does not explain the primary input (bom), output locations, or behavior of mode. The output schema exists but the description still lacks context for many parameters.
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?
With 0% schema description coverage, the description partially compensates by explaining the format parameter (TSV, CSV, JSON, Markdown) and the include_possible_matches parameter ('POSSIBLE_MATCH requires explicit opt-in'). However, it leaves the bom, mode, output_dir, and saved_path parameters undefined.
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 specifies the action ('Export'), the resource ('only VERIFIED_MATCH and VERIFIED_WITH_ASSUMPTION lines'), and the output formats (TSV, CSV, JSON, Markdown). It clearly distinguishes from sibling tools by focusing on exporting an order list.
Agents choose between tools based on descriptions. A clear purpose with a specific verb and resource helps agents select the right tool.
Usage Guidelines3/5
Does the description explain when to use this tool, when not to, or what alternatives exist?
The description implies when to use (for exporting certain verified lines) and provides a condition ('POSSIBLE_MATCH requires explicit opt-in'), but does not explicitly contrast with sibling tools or give guidance on when not to use this tool.
Agents often have multiple tools that could apply. Explicit usage guidance like "use X instead of Y when Z" prevents misuse.
Behavior3/5
Does the description disclose side effects, auth requirements, rate limits, or destructive behavior?
No annotations provided, so description must carry burden. It discloses that offline results are synthetic and not purchase-ready, but doesn't mention authentication, rate limits, or mode-specific behaviors.
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?
The description is concise with two sentences, no unnecessary words. However, it lacks structured formatting like bullet points for key aspects.
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 8 parameters with no schema descriptions and no output schema in context, the description is incomplete. It doesn't explain return values, pagination, or how to interpret results.
Complex tools with many parameters or behaviors need more documentation. Simple tools need less. This dimension scales expectations accordingly.
Parameters2/5
Does the description clarify parameter syntax, constraints, interactions, or defaults beyond what the schema provides?
Schema description coverage is 0%, yet the description adds no parameter-level detail. It mentions 'natural-language query' but doesn't explain parameters like mode, limit, or requirements.
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: search DigiKey candidates using natural language, enrich with ProductDetails, and preserve trade-offs. It distinguishes from sibling tools like building BOMs or comparing candidates.
Agents choose between tools based on descriptions. A clear purpose with a specific verb and resource helps agents select the right tool.
Usage Guidelines3/5
Does the description explain when to use this tool, when not to, or what alternatives exist?
The description lacks explicit when-to-use guidance or alternatives. It implies usage for initial part exploration but doesn't contrast with siblings like get_part_details or validate_bom.
Agents often have multiple tools that could apply. Explicit usage guidance like "use X instead of Y when Z" prevents misuse.
Behavior4/5
Does the description disclose side effects, auth requirements, rate limits, or destructive behavior?
With no annotations, the description provides behavioral details such as preserving unrelated lines and rerunning validation, but it omits side effects like auth requirements or performance constraints.
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?
The description is a single sentence that efficiently covers key actions with no wasted words.
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 output schema exists, the description sufficiently covers the tool's process, though it could mention that the output is an updated BOM.
Complex tools with many parameters or behaviors need more documentation. Simple tools need less. This dimension scales expectations accordingly.
Parameters2/5
Does the description clarify parameter syntax, constraints, interactions, or defaults beyond what the schema provides?
Schema coverage is 0%, and the description does not explain individual parameters beyond the requirement. It fails to compensate for the missing schema descriptions for bom, mode, output_dir, etc.
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 applies a new requirement to a structured BOM, preserves unrelated verified lines, explains invalidations/replacements, and reruns validation. This distinguishes it from siblings like digikey_build_electronics_bom and digikey_validate_bom.
Agents choose between tools based on descriptions. A clear purpose with a specific verb and resource helps agents select the right tool.
Usage Guidelines3/5
Does the description explain when to use this tool, when not to, or what alternatives exist?
The description implies usage when needing to add a requirement to an existing BOM, but it lacks explicit guidance on when to prefer this tool over alternatives or when not to use it.
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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