Open Source Intelligence MCP
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GitHub project health, package dependency risk, trending repos, license & package comparison.
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Tool Definition Quality
Average 4.2/5 across 7 of 7 tools scored. Lowest: 3.4/5.
Most tools have distinct purposes: package comparison, daily brief, dependency risk, license check, project health, trending repos, and protocol info. There is slight overlap between dependency_risk and project_health, but descriptions clarify different focuses (vulnerability vs. project vitality).
All tool names use lowercase with underscores (e.g., compare_packages, daily_brief). While not strictly verb_noun (some are noun_verb like license_check), the pattern is consistent across the set, aiding predictability.
7 tools cover the core areas of open-source intelligence (comparison, risk, health, trends, licensing, daily summary) without being overwhelming. Each tool has a clear role, and the count is well-scoped for the domain.
The tool surface covers major intelligence needs: package comparison, dependency risk, project health, trending repos, license checking, and a daily brief. Minor gaps exist (e.g., no individual package search, no security advisory tool), but the set is functional for common workflows.
Available Tools
7 toolscompare_packagesAInspect
Compare open-source packages (npm or PyPI) side by side in one ecosystem — downloads, maintenance status, dependents (community size), deprecation, license, and risk_score. The "which of these should I pick?" tool. Sources: PyPI, npm registry, libraries.io.
PAID: $0.01 USDC per query after the daily free allowance (25/day). On a 402, pay the returned Solana memo and re-call with the SAME args plus payment_tx=. An Authorization: Bearer fnet_ key bypasses it.
| Name | Required | Description | Default |
|---|---|---|---|
| agent_id | No | stable id for your agent (scopes the free-tier counter). | |
| packages | Yes | list of package names to compare (max 10). | |
| ecosystem | Yes | npm | pypi | cargo (applies to all packages). | |
| payment_tx | No | Solana tx signature, when re-calling after a 402. |
Output Schema
| Name | Required | Description |
|---|---|---|
No output parameters | ||
Tool Definition Quality
Does the description disclose side effects, auth requirements, rate limits, or destructive behavior?
With no annotations, the description carries full burden. It discloses payment model, sources, and error handling for 402. Missing details on rate limits or idempotency, but coverage is good given the tool's nature.
Agents need to know what a tool does to the world before calling it. Descriptions should go beyond structured annotations to explain consequences.
Is the description appropriately sized, front-loaded, and free of redundancy?
The description is front-loaded with core purpose and attributes. Payment details add length but are necessary. Could be more concise by separating payment into a note, but overall efficient.
Shorter descriptions cost fewer tokens and are easier for agents to parse. Every sentence should earn its place.
Given the tool's complexity, does the description cover enough for an agent to succeed on first attempt?
Given output schema exists and schema covers parameters, the description covers purpose, sources, payment, and 402 handling. Lacks mention of what happens when free allowance is exhausted without payment, but is fairly complete for the tool's complexity.
Complex tools with many parameters or behaviors need more documentation. Simple tools need less. This dimension scales expectations accordingly.
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 general context (compare packages, supported ecosystems) but does not add new meaning beyond the schema's parameter descriptions. Payment info is behavioral, not parameter-specific.
Input schemas describe structure but not intent. Descriptions should explain non-obvious parameter relationships and valid value ranges.
Does the description clearly state what the tool does and how it differs from similar tools?
The description clearly states it compares open-source packages side by side within one ecosystem, listing specific attributes (downloads, maintenance, dependents, etc.), sources, and positions it as a decision-support tool ('which of these should I pick?'). It distinguishes from sibling tools like dependency_risk and license_check.
Agents choose between tools based on descriptions. A clear purpose with a specific verb and resource helps agents select the right tool.
Does the description explain when to use this tool, when not to, or what alternatives exist?
The description indicates when to use (comparing multiple packages in the same ecosystem) and includes payment flow details (free daily allowance, 402 handling). However, it does not explicitly state when not to use or compare to siblings, but the context is clear.
Agents often have multiple tools that could apply. Explicit usage guidance like "use X instead of Y when Z" prevents misuse.
daily_briefAInspect
Get the curated daily open-source intelligence brief — the day's most significant signals in one package: top trending repos, notable dependency risks, newly deprecated packages, and the biggest-growth projects. From GitHub, PyPI, npm, and libraries.io. Each brief carries a MINT provenance attestation so a buyer can verify it was produced by this server, unaltered.
PAID: $5 USDC per brief. Defaults to today (UTC); a brief expires at the next midnight UTC. On a 402, pay the returned Solana memo and re-call with the SAME args plus payment_tx=. An Authorization: Bearer fnet_ key bypasses payment.
| Name | Required | Description | Default |
|---|---|---|---|
| date | No | brief date YYYY-MM-DD (default today, UTC). | |
| agent_id | No | stable id for your agent (scopes the free-tier counter). | |
| payment_tx | No | Solana tx signature, when re-calling after a 402. |
Output Schema
| Name | Required | Description |
|---|---|---|
No output parameters | ||
Tool Definition Quality
Does the description disclose side effects, auth requirements, rate limits, or destructive behavior?
No annotations provided, so description carries full burden. It discloses paid nature, daily expiration, payment flow using Solana memo and tx signature, authentication via fnet_ key, and MINT provenance attestation. No contradictions.
Agents need to know what a tool does to the world before calling it. Descriptions should go beyond structured annotations to explain consequences.
Is the description appropriately sized, front-loaded, and free of redundancy?
Description is well-structured with a clear main purpose followed by details on content, payment, and authentication. Somewhat verbose but front-loaded and free of redundancy.
Shorter descriptions cost fewer tokens and are easier for agents to parse. Every sentence should earn its place.
Given the tool's complexity, does the description cover enough for an agent to succeed on first attempt?
Given complexity (payment, authentication, expiration), the description covers all necessary behavioral and usage details. Output schema exists, so return values need not be explained. Complete for a paid, authentication-gated tool.
Complex tools with many parameters or behaviors need more documentation. Simple tools need less. This dimension scales expectations accordingly.
Does the description clarify parameter syntax, constraints, interactions, or defaults beyond what the schema provides?
Schema coverage is 100%, meeting baseline 3. Description adds context: date format (YYYY-MM-DD, default today UTC), agent_id for free-tier scoping, and payment_tx for re-calling after 402. This adds value beyond schema descriptions.
Input schemas describe structure but not intent. Descriptions should explain non-obvious parameter relationships and valid value ranges.
Does the description clearly state what the tool does and how it differs from similar tools?
The description clearly states the tool's purpose: 'Get the curated daily open-source intelligence brief' and lists specific content categories (trending repos, dependency risks, etc.), distinguishing it from sibling tools like trending_repos or dependency_risk.
Agents choose between tools based on descriptions. A clear purpose with a specific verb and resource helps agents select the right tool.
Does the description explain when to use this tool, when not to, or what alternatives exist?
Explicitly covers when to use (daily brief), payment details ($5 USDC, expiration), and a clear workflow for handling 402 errors with payment_tx parameter. Also mentions alternative authentication with an Authorization header.
Agents often have multiple tools that could apply. Explicit usage guidance like "use X instead of Y when Z" prevents misuse.
dependency_riskAInspect
Analyze dependency vulnerability/risk for a software package — maintenance status, last update, download trends, dependents, deprecation status, and a 0-100 risk_score (higher = riskier). The "should I add this dependency?" tool. Sources: PyPI, npm registry, libraries.io.
PAID: $0.02 USDC per query after the daily free allowance (25/day). On a 402, pay the returned Solana memo and re-call with the SAME args plus payment_tx=. An Authorization: Bearer fnet_ key bypasses it.
| Name | Required | Description | Default |
|---|---|---|---|
| agent_id | No | stable id for your agent (scopes the free-tier counter). | |
| ecosystem | Yes | npm | pypi | cargo. | |
| payment_tx | No | Solana tx signature, when re-calling after a 402. | |
| package_name | Yes | the package name, e.g. "express" or "requests". |
Output Schema
| Name | Required | Description |
|---|---|---|
No output parameters | ||
Tool Definition Quality
Does the description disclose side effects, auth requirements, rate limits, or destructive behavior?
No annotations provided, but description discloses payment behavior (cost, free allowance, 402 retry logic with Solana memo, and auth bypass) and data sources (PyPI, npm, libraries.io). This is crucial for agent decision-making.
Agents need to know what a tool does to the world before calling it. Descriptions should go beyond structured annotations to explain consequences.
Is the description appropriately sized, front-loaded, and free of redundancy?
Front-loaded with core purpose, then lists outputs, then explains payment flow. Every sentence adds value, though slightly verbose. Well-structured overall.
Shorter descriptions cost fewer tokens and are easier for agents to parse. Every sentence should earn its place.
Given the tool's complexity, does the description cover enough for an agent to succeed on first attempt?
Covers return values (six specific metrics), payment handling (cost, free limit, retry logic with memo and auth bypass), and data sources. With an output schema present, the description provides sufficient contextual completeness for an agent to use the tool correctly.
Complex tools with many parameters or behaviors need more documentation. Simple tools need less. This dimension scales expectations accordingly.
Does the description clarify parameter syntax, constraints, interactions, or defaults beyond what the schema provides?
Schema coverage is 100% so baseline is 3. However, description adds context for payment_tx (when to use after 402) and agent_id (scopes free counter), enhancing understanding beyond the schema definitions.
Input schemas describe structure but not intent. Descriptions should explain non-obvious parameter relationships and valid value ranges.
Does the description clearly state what the tool does and how it differs from similar tools?
Clearly states the tool analyzes dependency vulnerability/risk, lists specific metrics (maintenance status, risk score), and explicitly frames it as the 'should I add this dependency?' tool, distinguishing it from siblings like compare_packages or license_check.
Agents choose between tools based on descriptions. A clear purpose with a specific verb and resource helps agents select the right tool.
Does the description explain when to use this tool, when not to, or what alternatives exist?
Provides a clear use case ('should I add this dependency?') and context about pricing and payment flow, but does not explicitly mention when not to use it or compare to alternatives. Still, the purpose is well-defined.
Agents often have multiple tools that could apply. Explicit usage guidance like "use X instead of Y when Z" prevents misuse.
license_checkBInspect
Check open-source license compatibility for a GitHub repository — detected license type, permissions, restrictions, commercial-use eligibility, and compatibility guidance (permissive vs copyleft). Source: GitHub API. FREE.
| Name | Required | Description | Default |
|---|---|---|---|
| repo | Yes | GitHub repository as "owner/name", e.g. "facebook/react". | |
| agent_id | No | stable id for your agent (unused for free tools). | |
| payment_tx | No | unused (this tool is free). |
Output Schema
| Name | Required | Description |
|---|---|---|
No output parameters | ||
Tool Definition Quality
Does the description disclose side effects, auth requirements, rate limits, or destructive behavior?
No annotations provided. The description mentions the source (GitHub API) and that it's free, but does not disclose rate limits, authentication needs, or other behavioral traits beyond what is implied.
Agents need to know what a tool does to the world before calling it. Descriptions should go beyond structured annotations to explain consequences.
Is the description appropriately sized, front-loaded, and free of redundancy?
Single sentence with clear information, but it packs many details; could be slightly restructured for readability. Still efficient and front-loaded.
Shorter descriptions cost fewer tokens and are easier for agents to parse. Every sentence should earn its place.
Given the tool's complexity, does the description cover enough for an agent to succeed on first attempt?
Has output schema so return details not needed. Description covers tool function and source, but lacks when to use it or any prerequisites, leaving some gaps.
Complex tools with many parameters or behaviors need more documentation. Simple tools need less. This dimension scales expectations accordingly.
Does the description clarify parameter syntax, constraints, interactions, or defaults beyond what the schema provides?
Schema coverage is 100% with descriptions for each parameter. The description adds no new semantics beyond the schema, providing the baseline score of 3.
Input schemas describe structure but not intent. Descriptions should explain non-obvious parameter relationships and valid value ranges.
Does the description clearly state what the tool does and how it differs from similar tools?
The description explicitly states the tool checks open-source license compatibility for a GitHub repository and lists specific outputs (license type, permissions, restrictions, etc.). It clearly distinguishes from siblings like dependency_risk or project_health.
Agents choose between tools based on descriptions. A clear purpose with a specific verb and resource helps agents select the right tool.
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 siblings. While siblings are listed, there is no explicit when-to-use or when-not-to-use advice.
Agents often have multiple tools that could apply. Explicit usage guidance like "use X instead of Y when Z" prevents misuse.
mint_infoAInspect
FoundryNet Data Network info + MINT Protocol details. FREE.
Returns how to attest your agent's open-source analysis with MINT Protocol for verifiable on-chain proof, the MINT MCP endpoint, and the sister data servers (gov-contracts, brand-intel, patent-intel, financial-signals, weather-intel, cyber-intel, compliance, academic-intel, fact-check, social-intel).
| Name | Required | Description | Default |
|---|---|---|---|
No parameters | |||
Output Schema
| Name | Required | Description |
|---|---|---|
No output parameters | ||
Tool Definition Quality
Does the description disclose side effects, auth requirements, rate limits, or destructive behavior?
With no annotations, the description carries full burden. It describes outputs and mentions 'FREE', but does not explicitly state that it is read-only or safe. However, it is not misleading and provides basic behavioral context.
Agents need to know what a tool does to the world before calling it. Descriptions should go beyond structured annotations to explain consequences.
Is the description appropriately sized, front-loaded, and free of redundancy?
The description is concise with a front-loaded statement and a list of outputs. It is efficiently structured without unnecessary words, though could be slightly more streamlined.
Shorter descriptions cost fewer tokens and are easier for agents to parse. Every sentence should earn its place.
Given the tool's complexity, does the description cover enough for an agent to succeed on first attempt?
Given no parameters and the presence of an output schema, the description adequately explains what the tool returns. It does not mention authentication or prerequisites, but for a simple info tool, it is sufficiently complete.
Complex tools with many parameters or behaviors need more documentation. Simple tools need less. This dimension scales expectations accordingly.
Does the description clarify parameter syntax, constraints, interactions, or defaults beyond what the schema provides?
The tool has no parameters, and schema coverage is 100%. Per guidelines, 0 parameters gives a baseline of 4. The description adds no param info, which is acceptable since there are none.
Input schemas describe structure but not intent. Descriptions should explain non-obvious parameter relationships and valid value ranges.
Does the description clearly state what the tool does and how it differs from similar tools?
The description states the tool returns FoundryNet Data Network info and MINT Protocol details, listing specific outputs. It clearly distinguishes from sibling tools that focus on package analysis and project health. However, it lacks an explicit verb like 'retrieve' or 'get', but the purpose is clear.
Agents choose between tools based on descriptions. A clear purpose with a specific verb and resource helps agents select the right tool.
Does the description explain when to use this tool, when not to, or what alternatives exist?
The description implies usage when needing MINT protocol or FoundryNet info, as sibling tools cover different domains. However, it does not provide explicit guidance on when to use versus alternatives or any exclusions.
Agents often have multiple tools that could apply. Explicit usage guidance like "use X instead of Y when Z" prevents misuse.
project_healthAInspect
Check open-source project health for a GitHub repository — stars, forks, open issues, commit frequency, last commit date, contributor count, license, and a 0-100 composite health_score (popularity + activity + maintenance + governance). The "is this project alive and worth depending on?" tool. Source: GitHub API.
PAID: $0.01 USDC per query after a daily free allowance (25/day). On a 402, pay the returned Solana memo and re-call with the SAME args plus payment_tx=. agent_id scopes your allowance; an Authorization: Bearer fnet_ key bypasses it.
| Name | Required | Description | Default |
|---|---|---|---|
| repo | Yes | GitHub repository as "owner/name", e.g. "facebook/react". | |
| agent_id | No | stable id for your agent (scopes the free-tier counter). | |
| payment_tx | No | Solana tx signature, when re-calling after a 402. |
Output Schema
| Name | Required | Description |
|---|---|---|
No output parameters | ||
Tool Definition Quality
Does the description disclose side effects, auth requirements, rate limits, or destructive behavior?
With no annotations, the description fully carries the transparency burden. It discloses pricing ($0.01 USDC after free allowance), error handling (402 with payment_tx), authentication (agent_id and Bearer token), and data source (GitHub API). This is excellent disclosure of behavioral traits.
Agents need to know what a tool does to the world before calling it. Descriptions should go beyond structured annotations to explain consequences.
Is the description appropriately sized, front-loaded, and free of redundancy?
The description is somewhat lengthy but well-structured: starts with purpose, lists metrics, then adds pricing and retry logic. Every sentence provides value, though it could be slightly more concise without losing clarity.
Shorter descriptions cost fewer tokens and are easier for agents to parse. Every sentence should earn its place.
Given the tool's complexity, does the description cover enough for an agent to succeed on first attempt?
Given the presence of an output schema, the description does not need to explain return values. It covers the tool's purpose, pricing, authentication, error handling, and parameters comprehensively. It is complete for the complexity level.
Complex tools with many parameters or behaviors need more documentation. Simple tools need less. This dimension scales expectations accordingly.
Does the description clarify parameter syntax, constraints, interactions, or defaults beyond what the schema provides?
Schema coverage is 100%, so the baseline is 3. The description adds value beyond schema: provides example for repo (owner/name), explains payment_tx usage after 402, and clarifies agent_id scopies free tier. It doesn't add detail for agent_id format but is still helpful.
Input schemas describe structure but not intent. Descriptions should explain non-obvious parameter relationships and valid value ranges.
Does the description clearly state what the tool does and how it differs from similar tools?
The description clearly states the tool's purpose: checking open-source project health for a GitHub repository, listing specific metrics (stars, forks, open issues, etc.) and a composite health score. It distinguishes itself from siblings by focusing on GitHub and a composite score, making the purpose unambiguous.
Agents choose between tools based on descriptions. A clear purpose with a specific verb and resource helps agents select the right tool.
Does the description explain when to use this tool, when not to, or what alternatives exist?
The description explicitly frames the tool as answering 'is this project alive and worth depending on?' and provides payment and retry instructions. It does not directly compare to sibling tools like compare_packages or dependency_risk, but the use case is clear. Slightly lacking explicit when-not-to-use guidance.
Agents often have multiple tools that could apply. Explicit usage guidance like "use X instead of Y when Z" prevents misuse.
trending_reposAInspect
Find trending GitHub repositories with growth metrics (stars, forks, language, license) — optionally filtered by language or topic. Unfiltered queries are served from the daily-aggregated snapshot; filtered ones hit GitHub search live. Source: GitHub API.
PAID: $0.01 USDC per query after the daily free allowance (25/day). On a 402, pay the returned Solana memo and re-call with the SAME args plus payment_tx=. An Authorization: Bearer fnet_ key bypasses it.
| Name | Required | Description | Default |
|---|---|---|---|
| topic | No | filter by GitHub topic, e.g. "machine-learning". | |
| period | No | "daily" | "weekly" growth window (default weekly). | |
| agent_id | No | stable id for your agent (scopes the free-tier counter). | |
| language | No | filter by primary language, e.g. "python", "rust". | |
| payment_tx | No | Solana tx signature, when re-calling after a 402. |
Output Schema
| Name | Required | Description |
|---|---|---|
No output parameters | ||
Tool Definition Quality
Does the description disclose side effects, auth requirements, rate limits, or destructive behavior?
No annotations provided, so description fully carries burden. Discloses data source, performance trade-offs, cost model, free allowance, 402 handling with retry logic, and auth bypass. Comprehensive.
Agents need to know what a tool does to the world before calling it. Descriptions should go beyond structured annotations to explain consequences.
Is the description appropriately sized, front-loaded, and free of redundancy?
Three focused sentences plus payment instructions. Front-loaded with purpose. Efficient but could be more structured. No unnecessary text.
Shorter descriptions cost fewer tokens and are easier for agents to parse. Every sentence should earn its place.
Given the tool's complexity, does the description cover enough for an agent to succeed on first attempt?
Output schema exists. Description covers purpose, behavior, error handling, and payment. Complete for a tool with this complexity.
Complex tools with many parameters or behaviors need more documentation. Simple tools need less. This dimension scales expectations accordingly.
Does the description clarify parameter syntax, constraints, interactions, or defaults beyond what the schema provides?
Schema coverage is 100% with descriptions for each parameter. Description adds context on performance implications (snapshot vs live) but does not significantly extend beyond schema.
Input schemas describe structure but not intent. Descriptions should explain non-obvious parameter relationships and valid value ranges.
Does the description clearly state what the tool does and how it differs from similar tools?
Clear verb ('Find') and resource ('trending GitHub repositories') with specifics on growth metrics and optional filters. Distinct from sibling tools like compare_packages or daily_brief.
Agents choose between tools based on descriptions. A clear purpose with a specific verb and resource helps agents select the right tool.
Does the description explain when to use this tool, when not to, or what alternatives exist?
Provides context on when to use filtered vs unfiltered (snapshot vs live) and payment handling, but no explicit guidance on when to choose this tool over alternatives.
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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