Fact Verification MCP
Server Details
Verify claims with verdict, confidence & cited sources; batch verify, source checks, daily brief.
- Status
- Unhealthy
- Last Tested
- Transport
- Streamable HTTP
- URL
Glama MCP Gateway
Connect through Glama MCP Gateway for full control over tool access and complete visibility into every call.
Full call logging
Every tool call is logged with complete inputs and outputs, so you can debug issues and audit what your agents are doing.
Tool access control
Enable or disable individual tools per connector, so you decide what your agents can and cannot do.
Managed credentials
Glama handles OAuth flows, token storage, and automatic rotation, so credentials never expire on your clients.
Usage analytics
See which tools your agents call, how often, and when, so you can understand usage patterns and catch anomalies.
Tool Definition Quality
Average 4.4/5 across 6 of 6 tools scored. Lowest: 3.9/5.
Each tool targets a distinct aspect of fact verification: single/batch claims, source credibility, briefs, and network info. No two tools have overlapping purposes, so an agent can clearly differentiate them.
All names use snake_case and are descriptive, but they mix verb_noun patterns (batch_verify, source_check, verify_claim) with noun_noun patterns (brief_summary, daily_brief, mint_info). The variation is minor and does not hinder readability.
With 6 tools, the server covers the core workflows of fact verification without being bloated. The count feels well-scoped for the domain, and each tool serves a necessary function.
The set covers verification, source checking, batch processing, and briefs. However, there may be missing tools for managing past verifications or editing claims, though the core lifecycle is addressed. Minor gaps, but agents can still accomplish key tasks.
Available Tools
6 toolsbatch_verifyAInspect
Verify many factual claims in one batch fact-check call. Returns an array of verify_claim results (verdict + confidence + cited sources + explanation), each cross-referencing web search and the FoundryNet data network, plus the batch pricing and a MINT provenance attestation over the whole batch. Each claim is cached for 24h, so repeats are cheap.
PAID: $0.01 USDC per claim, minimum $0.05 USDC per batch, after the daily free allowance (10/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 |
|---|---|---|---|
| claims | Yes | array of claim strings (1-50). | |
| 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 the description fully handles behavioral disclosure. It reveals the tool is paid, caches claims for 24h, requires Solana payment on 402, and returns cross-referenced results. Lacks rate limits but is otherwise transparent.
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 well-structured with a clear main purpose sentence followed by payment details in a separate paragraph. Though slightly lengthy, every sentence adds value. Front-loads the core function.
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 tool's complexity (payment, caching, error handling), the description covers most aspects. Output schema exists but description already summarizes return values. Could mention rate limits or auth key format but is otherwise 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?
Schema coverage is 100%, but the description adds meaningful context: claims array size (1-50), agent_id scopes free counter, payment_tx usage for retries. It explains the payment flow beyond 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?
The description clearly states 'Verify many factual claims in one batch fact-check call,' specifying the verb (verify), resource (claims), and scope (batch). It distinguishes from sibling tools like verify_claim and source_check by focusing on batch processing.
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 includes detailed payment instructions, free allowance, caching policy, and how to handle 402 errors with payment_tx. It implicitly guides when to use (batch vs single via siblings) but could explicitly state not to use for single claims.
Agents often have multiple tools that could apply. Explicit usage guidance like "use X instead of Y when Z" prevents misuse.
brief_summaryAInspect
Get the top 5 signals from today's brief as structured JSON — a cheap sample of the full daily_brief. Returns the day's highest-priority items (no prose) so an agent can decide whether to buy the full brief.
PAID: $0.50 USDC (vs the full daily_brief price). Defaults to today (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?
The description discloses key behavioral traits: returns structured JSON (no prose), defaults to today UTC, costs $0.50 USDC (unless auth key bypasses payment), and describes the 402 payment flow with re-call using payment_tx. Since no annotations are provided, the description carries the full burden and does so thoroughly, though rate limits or idempotency are not mentioned.
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 (four sentences) and front-loaded with the core purpose. Every sentence adds value, covering purpose, cost, default behavior, and payment/auth details with no 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?
The description covers the tool's purpose, output format, cost, default date, payment flow, and auth bypass. It omits rate limits and idempotency, but the presence of an output schema reduces the need to describe return values. Given the tool's complexity (payment, error handling, free-tier scoping), the description is largely 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?
Schema coverage is 100%, so the schema already describes each parameter. The description adds context: date defaults to today (UTC), agent_id scopes the free-tier counter, and payment_tx is used in the 402 re-call flow. This clarifies usage beyond the schema, especially the payment_tx workflow.
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 returns the top 5 signals from today's brief as structured JSON, serving as a cheap sample of the full daily_brief. It distinguishes from sibling daily_brief by specifying it's a cheaper subset with no prose.
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 explains when to use this tool (to decide whether to buy the full brief) and provides context on default date, payment requirements, and error handling. However, it does not explicitly state when not to use it or list alternatives beyond the implicit reference to daily_brief.
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 fact-check brief — the day's claim-verification signals in one package: the top disputed claims, the most-verified claims, the trending topics being checked, and counts by verdict + domain. 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 (x402 rail). | |
| stripe_token | No | Stripe Checkout Session id (cs_…), when re-calling after paying the Stripe payment link (alternative to x402). Can also be supplied via the X-Stripe-Token header. |
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 were provided, so the description fully bears the burden. It discloses the paid nature, expiry behavior, provenance attestation, and the x402 payment flow. It also mentions the agent_id scopes a free-tier counter. No contradictions are present.
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 well-structured into two paragraphs (content overview and payment instructions) and front-loads the purpose. However, it is somewhat lengthy; the payment details could be slightly more streamlined 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 complexity of payment, expiry, multiple payment methods, and provenance attestation, the description covers all necessary aspects. An output schema exists, so return value details are not needed here. The description is sufficiently complete for an AI agent to correctly select and invoke the 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% with descriptions for each parameter. The description adds context beyond the schema by explaining the payment flow for 'payment_tx' and 'stripe_token', and clarifying that 'date' defaults to today UTC and 'agent_id' scopes the free-tier counter. This extra context justifies a score above the baseline 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 clearly states that this tool retrieves a curated daily fact-check brief with specific components (top disputed claims, most-verified claims, trending topics, verdict/domain counts) and a provenance attestation. It distinguishes itself from siblings like 'verify_claim' by being a summary rather than single-claim verification.
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 provides explicit when-to-use guidance (to get the daily brief), payment requirements ($5 USDC per brief, defaults to today, expires at midnight UTC), and detailed instructions on handling 402 errors (pay Solana memo and re-call with payment_tx; alternative token-based bypass). It also mentions alternative payment via Stripe token.
Agents often have multiple tools that could apply. Explicit usage guidance like "use X instead of Y when Z" prevents misuse.
mint_infoAInspect
Get FoundryNet Data Network info + MINT Protocol attestation details. FREE.
Returns how to attest your agent's fact-verification results with MINT Protocol for verifiable on-chain proof, the MINT MCP endpoint, and the sister data servers across the full FoundryNet Data Network (financial-signals, cyber-intel, patent-intel, gov-contracts, compliance, brand-intel, weather-intel, academic-intel, oss-intel, 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?
The description says 'FREE' and describes the return content, but with no annotations, it fails to disclose auth requirements or rate limits. It does not contradict any annotation.
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 the core purpose and is concise, covering key elements without unnecessary words.
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?
The description adequately explains the tool's output given its simplicity. However, it could be more specific about the exact fields returned, but with an output schema present, it is acceptable.
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?
With zero parameters, the schema is empty. The description adds value by detailing the returned information, achieving a baseline score of 4.
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 'Get FoundryNet Data Network info + MINT Protocol attestation details', providing a specific verb and resource. It distinguishes from sibling tools like verify_claim which focus on verification.
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 explicit when-to-use guidance is provided. The description implies it provides foundational info for attestation but does not compare with alternatives like daily_brief or source_check.
Agents often have multiple tools that could apply. Explicit usage guidance like "use X instead of Y when Z" prevents misuse.
source_checkAInspect
Check a source URL's credibility and trustworthiness for source verification — domain age (via RDAP), trust signals, bias indicators, and publication history. Use it to weight whether a citation is trustworthy. Results carry a MINT provenance attestation and are cached for 24h.
PAID: $0.01 USDC per check after the daily free allowance (10/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 |
|---|---|---|---|
| url | Yes | the source URL or domain to assess, e.g. "https://reuters.com/...". | |
| 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, but the description fully discloses behavioral traits: MINT provenance attestation, 24h cache, payment model ($0.01 after 10/day), 402 handling, and key bypass. This covers all necessary aspects for safe usage.
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 a single paragraph of 6 sentences, front-loaded with purpose, and each sentence adds unique value. No wasted words.
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 tool's complexity (3 parameters, output schema, payment model), the description covers purpose, usage, caching, error handling, and authentication, making it complete for agent invocation.
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 description coverage is 100%, and the description adds value beyond schema by explaining the payment flow (agent_id scopes free counter, payment_tx for 402 retry). This helps the agent use parameters correctly.
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 checks a source URL's credibility and trustworthiness, specifying domain age, trust signals, bias indicators, and publication history. It distinguishes from siblings like batch_verify and verify_claim by focusing on source verification.
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 says 'Use it to weight whether a citation is trustworthy' and provides payment instructions. However, it does not mention when not to use or compare with sibling tools.
Agents often have multiple tools that could apply. Explicit usage guidance like "use X instead of Y when Z" prevents misuse.
verify_claimAInspect
Verify a factual claim and return a verdict, confidence score, and cited sources. Classifies the claim's domain (company / finance / patents / regulation), cross-references web search and the relevant FoundryNet data network source, and returns a verdict (supported | disputed | unverifiable) with a 0-100 confidence, the cited sources, and a short explanation. Results carry a MINT provenance attestation and are cached for 24h.
PAID: $0.02 USDC per verification after a daily free allowance (10/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 |
|---|---|---|---|
| claim | Yes | the factual statement to verify, e.g. "Acme Corp was founded in 2009". | |
| context | No | optional extra context that disambiguates the claim. | |
| 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 carries full burden. It discloses paid usage, free allowance, caching (24h), 402 retry mechanism, provenance attestation, and that agent_id scopes allowance. It does not explicitly state read-only nature, but the behavior is well-covered.
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 two paragraphs: first focuses on core functionality, second on payment details. It is front-loaded and each sentence adds value, though it could be slightly more concise.
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 4 parameters (1 required), presence of output schema, and no annotations, the description covers all needed context: what the tool does, how to handle payment, caching, and domain classification. No essential information is missing.
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% and description adds meaning: explains agent_id's role in scoping free tier, payment_tx for re-calls, and context as disambiguation. It provides functional context beyond parameter names and types.
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 verb 'verify' and resource 'factual claim', and outlines the return values (verdict, confidence, sources). It implies differentiation from siblings like batch_verify (single vs batch) but does not explicitly distinguish, so not a 5.
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 clearly states when to use (to verify a factual claim) and provides context on cost and retry logic, but does not explicitly mention when not to use or offer alternatives among siblings.
Agents often have multiple tools that could apply. Explicit usage guidance like "use X instead of Y when Z" prevents misuse.
Claim this connector by publishing a /.well-known/glama.json file on your server's domain with the following structure:
{
"$schema": "https://glama.ai/mcp/schemas/connector.json",
"maintainers": [{ "email": "your-email@example.com" }]
}The email address must match the email associated with your Glama account. Once published, Glama will automatically detect and verify the file within a few minutes.
Control your server's listing on Glama, including description and metadata
Access analytics and receive server usage reports
Get monitoring and health status updates for your server
Feature your server to boost visibility and reach more users
For users:
Full audit trail – every tool call is logged with inputs and outputs for compliance and debugging
Granular tool control – enable or disable individual tools per connector to limit what your AI agents can do
Centralized credential management – store and rotate API keys and OAuth tokens in one place
Change alerts – get notified when a connector changes its schema, adds or removes tools, or updates tool definitions, so nothing breaks silently
For server owners:
Proven adoption – public usage metrics on your listing show real-world traction and build trust with prospective users
Tool-level analytics – see which tools are being used most, helping you prioritize development and documentation
Direct user feedback – users can report issues and suggest improvements through the listing, giving you a channel you would not have otherwise
The connector status is unhealthy when Glama is unable to successfully connect to the server. This can happen for several reasons:
The server is experiencing an outage
The URL of the server is wrong
Credentials required to access the server are missing or invalid
If you are the owner of this MCP connector and would like to make modifications to the listing, including providing test credentials for accessing the server, please contact support@glama.ai.
Discussions
No comments yet. Be the first to start the discussion!